Fall 2025
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GenAI Code
GenAI Code
AI for Coders — only learning from the best will give you a real edge
Build advanced AI applications and open the door to an international career. This 6-week course will equip you with the skills you need to create solutions powered by generative artificial intelligence (GenAI). You’ll gain hands-on experience working with images, text, and audio, integrating models with various data sources (RAG), implementing LLMs, monitoring and evaluating their performance, and deploying them in the cloud.
Included in the program:
RAG
Included in the program:
RAG
+
participants on previous editions
+
members of Elephant AI community
Included in the program:
RAG
Included in the program:
RAG
Included in the program:
RAG
Course positively verified by people working for major brands:
Course positively verified by people working for major brands:
Course positively verified by people working for major brands:
Course positively verified by people working for major brands:
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
6 weeks of learning together
You learn in a group, not alone. Elephant AI is built around a community that learns together. In addition to LIVE sessions, you’ll take part in daily discussions, Q&As, and knowledge-sharing with other students.
340+ ambitious alumni
The next edition of the GenAI Code course is planned for: Q2 2025. Just starting to code? No problem! We’ll provide you with materials to help you prepare for the course and gain the required skills.
Konrad Banachewicz, PhD & Special Guests
Kaggle Grandmaster and seasoned Machine Learning expert. He’ll be joined by international guests — global stars of Machine Learning and Artificial Intelligence.
What will you learn on the course?
Imagine a scenario where you have the skills top companies around the world are looking for — and you're opening the door to an exciting career in artificial intelligence.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
What will you learn on the course?
Imagine a scenario where you have the skills top companies around the world are looking for — and you're opening the door to an exciting career in artificial intelligence.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
What will you learn on the course?
Imagine a scenario where you have the skills top companies around the world are looking for — and you're opening the door to an exciting career in artificial intelligence.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
What will you learn on the course?
Imagine a scenario where you have the skills top companies around the world are looking for — and you're opening the door to an exciting career in artificial intelligence.
Generative AI in Practice
You’ll build impressive projects and applications using GenAI to solve a variety of real-world problems.
Large Language Models (LLMs)
You’ll gain hands-on knowledge about evaluating, selecting, and implementing LLMs, enabling you to use this revolutionary technology in real projects.
Integrating AI with Real-World Data
You’ll learn how to connect AI models with external data sources (RAG) and deploy them as complete cloud-based solutions.
Unconventional Approach to Programming
You’ll move beyond traditional patterns and explore new, innovative methods that will help you create breakthrough GenAI-based applications and solutions.
Learn from the Best
Our instructors are experienced experts in GenAI who have earned recognition in prestigious Kaggle competitions. They’ll share their knowledge and skills to help you grow your coding toolkit.
International Career
You’ll strengthen your CV with in-demand, globally recognized AI skills. Get ready to work in major corporations and take your career to the next level.
We're making AGI and it will be 'worth it.' 'Don't care if we burn $500M or $50B.
~
Sam Altman
OpenAI CEO
Generative AI is the most powerful tool for creativity that has ever been created. It has the potential to unleash a new era of human innovation.
~
Elon Musk
SpaceX
Generative AI ‘FOMO’ is driving tech heavyweights to invest billions of dollars in startups
~
Hayden Field
CNBC
We're making AGI and it will be 'worth it.' 'Don't care if we burn $500M or $50B.
~
Sam Altman
OpenAI CEO
Generative AI is the most powerful tool for creativity that has ever been created. It has the potential to unleash a new era of human innovation.
~
Elon Musk
SpaceX
Generative AI ‘FOMO’ is driving tech heavyweights to invest billions of dollars in startups
~
Hayden Field
CNBC
We're making AGI and it will be 'worth it.' 'Don't care if we burn $500M or $50B.
~
Sam Altman
OpenAI CEO
Generative AI is the most powerful tool for creativity that has ever been created. It has the potential to unleash a new era of human innovation.
~
Elon Musk
SpaceX
Generative AI ‘FOMO’ is driving tech heavyweights to invest billions of dollars in startups
~
Hayden Field
CNBC
We're making AGI and it will be 'worth it.' 'Don't care if we burn $500M or $50B.
~
Sam Altman
OpenAI CEO
Generative AI is the most powerful tool for creativity that has ever been created. It has the potential to unleash a new era of human innovation.
~
Elon Musk
SpaceX
Generative AI ‘FOMO’ is driving tech heavyweights to invest billions of dollars in startups
~
Hayden Field
CNBC
GenAI Code. Take control of AI
We assume you have basic programming knowledge that allows you to communicate with APIs — ideally in Python (lists, dictionaries) — and that you have experience with libraries such as scikit-learn. The GenAI Code course was created for:
Beginner developers looking to gain solid, hands-on experience in GenAI
Experienced software engineers who want to expand their skills in generative AI
People interested in building an international tech career
Anyone who wants to harness revolutionary technology to solve real-world problems
GenAI Code. Take control of AI
We assume you have basic programming knowledge that allows you to communicate with APIs — ideally in Python (lists, dictionaries) — and that you have experience with libraries such as scikit-learn. The GenAI Code course was created for:
Beginner developers looking to gain solid, hands-on experience in GenAI
Experienced software engineers who want to expand their skills in generative AI
People interested in building an international tech career
Anyone who wants to harness revolutionary technology to solve real-world problems
GenAI Code. Take control of AI
We assume you have basic programming knowledge that allows you to communicate with APIs — ideally in Python (lists, dictionaries) — and that you have experience with libraries such as scikit-learn. The GenAI Code course was created for:
Beginner developers looking to gain solid, hands-on experience in GenAI
Experienced software engineers who want to expand their skills in generative AI
People interested in building an international tech career
Anyone who wants to harness revolutionary technology to solve real-world problems
GenAI Code. Take control of AI
We assume you have basic programming knowledge that allows you to communicate with APIs — ideally in Python (lists, dictionaries) — and that you have experience with libraries such as scikit-learn. The GenAI Code course was created for:
Beginner developers looking to gain solid, hands-on experience in GenAI
Experienced software engineers who want to expand their skills in generative AI
People interested in building an international tech career
Anyone who wants to harness revolutionary technology to solve real-world problems
GenAI is something that really helps us support our daily work in a meaningful way. (...) I took part in the earlier course (AI for Managers), which truly gave me a solid background in areas I was missing — including the technical basics and the terminology needed to actually understand what it's all about.
~
Karolina Wilamowska
Technology Advocate
GenAI is something that really helps us support our daily work in a meaningful way. (...) I took part in the earlier course (AI for Managers), which truly gave me a solid background in areas I was missing — including the technical basics and the terminology needed to actually understand what it's all about.
~
Karolina Wilamowska
Technology Advocate
GenAI is something that really helps us support our daily work in a meaningful way. (...) I took part in the earlier course (AI for Managers), which truly gave me a solid background in areas I was missing — including the technical basics and the terminology needed to actually understand what it's all about.
~
Karolina Wilamowska
Technology Advocate
GenAI is something that really helps us support our daily work in a meaningful way. (...) I took part in the earlier course (AI for Managers), which truly gave me a solid background in areas I was missing — including the technical basics and the terminology needed to actually understand what it's all about.
~
Karolina Wilamowska
Technology Advocate
Get ready for the course and watch Maria Parysz's free webinars.
The new rules of business are emerging, AI is taking over and decisions are being made. Don't miss this moment. Learn how to use not only ChatGPT and GenAI, but also other AI technologies that are about to flood our market. Quickly upgrade your skills to manage AI projects, build products or startups based on artificial intelligence and data science. Show everyone that you can put ChatGPT and other innovations to work while others are still figuring out how to use them.
Get ready for the course and watch Maria Parysz's free webinars.
The new rules of business are emerging, AI is taking over and decisions are being made. Don't miss this moment. Learn how to use not only ChatGPT and GenAI, but also other AI technologies that are about to flood our market. Quickly upgrade your skills to manage AI projects, build products or startups based on artificial intelligence and data science. Show everyone that you can put ChatGPT and other innovations to work while others are still figuring out how to use them.
Get ready for the course and watch Maria Parysz's free webinars.
The new rules of business are emerging, AI is taking over and decisions are being made. Don't miss this moment. Learn how to use not only ChatGPT and GenAI, but also other AI technologies that are about to flood our market. Quickly upgrade your skills to manage AI projects, build products or startups based on artificial intelligence and data science. Show everyone that you can put ChatGPT and other innovations to work while others are still figuring out how to use them.
Get ready for the course and watch Maria Parysz's free webinars.
The new rules of business are emerging, AI is taking over and decisions are being made. Don't miss this moment. Learn how to use not only ChatGPT and GenAI, but also other AI technologies that are about to flood our market. Quickly upgrade your skills to manage AI projects, build products or startups based on artificial intelligence and data science. Show everyone that you can put ChatGPT and other innovations to work while others are still figuring out how to use them.
GenAI brings new possibilities that simply didn’t exist before — and most importantly, it’s accessible to everyone. With relatively little effort, you can create something new, something truly unique. What’s more, GenAI saves us time and lets us focus on other, more important things.
~
Benjamin Kadzioch
IT Project Manager
GenAI brings new possibilities that simply didn’t exist before — and most importantly, it’s accessible to everyone. With relatively little effort, you can create something new, something truly unique. What’s more, GenAI saves us time and lets us focus on other, more important things.
~
Benjamin Kadzioch
IT Project Manager
GenAI brings new possibilities that simply didn’t exist before — and most importantly, it’s accessible to everyone. With relatively little effort, you can create something new, something truly unique. What’s more, GenAI saves us time and lets us focus on other, more important things.
~
Benjamin Kadzioch
IT Project Manager
GenAI brings new possibilities that simply didn’t exist before — and most importantly, it’s accessible to everyone. With relatively little effort, you can create something new, something truly unique. What’s more, GenAI saves us time and lets us focus on other, more important things.
~
Benjamin Kadzioch
IT Project Manager
Do you buy courses and then leave them on the shelf?
With Elephant AI, it will be different.
There are areas where knowledge evolves extremely fast — and AI is one of them.
That’s why we chose a cohort-based course model.
In this setup, participants form a group led by trainers, working together toward mastering the topic. We share knowledge in small, manageable portions — every single day.
Additionally, cohort members build a real community. We discuss challenges together and help each other solve them.
In traditional online courses, you might find homework — but no one checks it because it would require too much work from the instructors. In a cohort, it's different. Every project you submit will be reviewed, and you’ll receive your certificate only after a positive evaluation. Throughout the course, you’ll receive a variety of learning materials. You decide which ones interest you most and how you want to use them.
Do you buy courses and then leave them on the shelf?
With Elephant AI, it will be different.
There are areas where knowledge evolves extremely fast — and AI is one of them.
That’s why we chose a cohort-based course model.
In this setup, participants form a group led by trainers, working together toward mastering the topic. We share knowledge in small, manageable portions — every single day.
Additionally, cohort members build a real community. We discuss challenges together and help each other solve them.
In traditional online courses, you might find homework — but no one checks it because it would require too much work from the instructors. In a cohort, it's different. Every project you submit will be reviewed, and you’ll receive your certificate only after a positive evaluation. Throughout the course, you’ll receive a variety of learning materials. You decide which ones interest you most and how you want to use them.
Do you buy courses and then leave them on the shelf?
With Elephant AI, it will be different.
There are areas where knowledge evolves extremely fast — and AI is one of them.
That’s why we chose a cohort-based course model.
In this setup, participants form a group led by trainers, working together toward mastering the topic. We share knowledge in small, manageable portions — every single day.
Additionally, cohort members build a real community. We discuss challenges together and help each other solve them.
In traditional online courses, you might find homework — but no one checks it because it would require too much work from the instructors. In a cohort, it's different. Every project you submit will be reviewed, and you’ll receive your certificate only after a positive evaluation. Throughout the course, you’ll receive a variety of learning materials. You decide which ones interest you most and how you want to use them.
Do you buy courses and then leave them on the shelf?
With Elephant AI, it will be different.
There are areas where knowledge evolves extremely fast — and AI is one of them.
That’s why we chose a cohort-based course model.
In this setup, participants form a group led by trainers, working together toward mastering the topic. We share knowledge in small, manageable portions — every single day.
Additionally, cohort members build a real community. We discuss challenges together and help each other solve them.
In traditional online courses, you might find homework — but no one checks it because it would require too much work from the instructors. In a cohort, it's different. Every project you submit will be reviewed, and you’ll receive your certificate only after a positive evaluation. Throughout the course, you’ll receive a variety of learning materials. You decide which ones interest you most and how you want to use them.
What does a course with Elephant AI look like?
1
6 weeks of collaborative learning
Elephant AI is a cohort-based program where we learn together. You’ll join a group of hundreds of students with similar goals and a shared passion for exploring how to use GenAI in real projects.
2
Evening live sessions
At the heart of the program are 10 live sessions held in the evenings on Zoom, every Monday and Wednesday.
You can expect practical exercises, Q&A, and active knowledge-sharing with fellow participants. The workshops will be led by Konrad Banachewicz along with special guest speakers, and each session will last around 2 hours. All live sessions will be recorded, so you won’t miss a thing.
3
Homework assignments
Almost every class wraps up with a homework assignment — a practical task where you demonstrate your new skills. Completing these assignments will be required to finish the course.
4
Final challenge
At the end of the program, you’ll take part in a data science challenge and compete with fellow participants. This competition will be a required part of course completion.
5
Deployment
In this course, you’ll learn how to build solutions ready for deployment in real-world environments. Instead of simple exercises, you’ll work on projects that reflect actual business challenges — learning implementation, testing, and deployment step by step.
6
Build real, commercial-ready products
This is a hands-on course — we’ll teach you how to create a complete, market-ready product. From the first line of code to core features and full integration, every task mirrors the real-life process of building applications that are ready for immediate use.
7
Prep materials
You’ll get access to curated resources to help you prepare for the course — whether you're a beginner or just want to refresh your skills.
8
DIY scripts
Our custom scripts will guide you in building your own models — for example, an LLM model aligned with the AI Act.
9
Progress feedback
With hundreds of AI enthusiasts in the program, we create space for peer reviews between participants so you can get feedback and improve continuously.
10
The Elephant AI community
You’ll learn as part of a community, not on your own. Our program is designed around a collaborative environment over the 6-week course. You’ll take part in daily discussions on the platform, Q&A sessions, and active knowledge exchange.
What does a course with Elephant AI look like?
1
6 weeks of collaborative learning
Elephant AI is a cohort-based program where we learn together. You’ll join a group of hundreds of students with similar goals and a shared passion for exploring how to use GenAI in real projects.
2
Evening live sessions
At the heart of the program are 10 live sessions held in the evenings on Zoom, every Monday and Wednesday.
You can expect practical exercises, Q&A, and active knowledge-sharing with fellow participants. The workshops will be led by Konrad Banachewicz along with special guest speakers, and each session will last around 2 hours. All live sessions will be recorded, so you won’t miss a thing.
3
Homework assignments
Almost every class wraps up with a homework assignment — a practical task where you demonstrate your new skills. Completing these assignments will be required to finish the course.
4
Final challenge
At the end of the program, you’ll take part in a data science challenge and compete with fellow participants. This competition will be a required part of course completion.
5
Deployment
In this course, you’ll learn how to build solutions ready for deployment in real-world environments. Instead of simple exercises, you’ll work on projects that reflect actual business challenges — learning implementation, testing, and deployment step by step.
6
Build real, commercial-ready products
This is a hands-on course — we’ll teach you how to create a complete, market-ready product. From the first line of code to core features and full integration, every task mirrors the real-life process of building applications that are ready for immediate use.
7
Prep materials
You’ll get access to curated resources to help you prepare for the course — whether you're a beginner or just want to refresh your skills.
8
DIY scripts
Our custom scripts will guide you in building your own models — for example, an LLM model aligned with the AI Act.
9
Progress feedback
With hundreds of AI enthusiasts in the program, we create space for peer reviews between participants so you can get feedback and improve continuously.
10
The Elephant AI community
You’ll learn as part of a community, not on your own. Our program is designed around a collaborative environment over the 6-week course. You’ll take part in daily discussions on the platform, Q&A sessions, and active knowledge exchange.
What does a course with Elephant AI look like?
1
6 weeks of collaborative learning
Elephant AI is a cohort-based program where we learn together. You’ll join a group of hundreds of students with similar goals and a shared passion for exploring how to use GenAI in real projects.
2
Evening live sessions
At the heart of the program are 10 live sessions held in the evenings on Zoom, every Monday and Wednesday.
You can expect practical exercises, Q&A, and active knowledge-sharing with fellow participants. The workshops will be led by Konrad Banachewicz along with special guest speakers, and each session will last around 2 hours. All live sessions will be recorded, so you won’t miss a thing.
3
Homework assignments
Almost every class wraps up with a homework assignment — a practical task where you demonstrate your new skills. Completing these assignments will be required to finish the course.
4
Final challenge
At the end of the program, you’ll take part in a data science challenge and compete with fellow participants. This competition will be a required part of course completion.
5
Deployment
In this course, you’ll learn how to build solutions ready for deployment in real-world environments. Instead of simple exercises, you’ll work on projects that reflect actual business challenges — learning implementation, testing, and deployment step by step.
6
Build real, commercial-ready products
This is a hands-on course — we’ll teach you how to create a complete, market-ready product. From the first line of code to core features and full integration, every task mirrors the real-life process of building applications that are ready for immediate use.
7
Prep materials
You’ll get access to curated resources to help you prepare for the course — whether you're a beginner or just want to refresh your skills.
8
DIY scripts
Our custom scripts will guide you in building your own models — for example, an LLM model aligned with the AI Act.
9
Progress feedback
With hundreds of AI enthusiasts in the program, we create space for peer reviews between participants so you can get feedback and improve continuously.
10
The Elephant AI community
You’ll learn as part of a community, not on your own. Our program is designed around a collaborative environment over the 6-week course. You’ll take part in daily discussions on the platform, Q&A sessions, and active knowledge exchange.
What does a course with Elephant AI look like?
1
6 weeks of collaborative learning
Elephant AI is a cohort-based program where we learn together. You’ll join a group of hundreds of students with similar goals and a shared passion for exploring how to use GenAI in real projects.
2
Evening live sessions
At the heart of the program are 10 live sessions held in the evenings on Zoom, every Monday and Wednesday.
You can expect practical exercises, Q&A, and active knowledge-sharing with fellow participants. The workshops will be led by Konrad Banachewicz along with special guest speakers, and each session will last around 2 hours. All live sessions will be recorded, so you won’t miss a thing.
3
Homework assignments
Almost every class wraps up with a homework assignment — a practical task where you demonstrate your new skills. Completing these assignments will be required to finish the course.
4
Final challenge
At the end of the program, you’ll take part in a data science challenge and compete with fellow participants. This competition will be a required part of course completion.
5
Deployment
In this course, you’ll learn how to build solutions ready for deployment in real-world environments. Instead of simple exercises, you’ll work on projects that reflect actual business challenges — learning implementation, testing, and deployment step by step.
6
Build real, commercial-ready products
This is a hands-on course — we’ll teach you how to create a complete, market-ready product. From the first line of code to core features and full integration, every task mirrors the real-life process of building applications that are ready for immediate use.
7
Prep materials
You’ll get access to curated resources to help you prepare for the course — whether you're a beginner or just want to refresh your skills.
8
DIY scripts
Our custom scripts will guide you in building your own models — for example, an LLM model aligned with the AI Act.
9
Progress feedback
With hundreds of AI enthusiasts in the program, we create space for peer reviews between participants so you can get feedback and improve continuously.
10
The Elephant AI community
You’ll learn as part of a community, not on your own. Our program is designed around a collaborative environment over the 6-week course. You’ll take part in daily discussions on the platform, Q&A sessions, and active knowledge exchange.
6 weeks full of knowledge, case studies, and community interaction
Today, understanding AI largely depends on how well the context is explained. During the Elephant AI course, we’ll share our best tactics — and there’s a good chance that, together with the whole group of participants, we’ll discover completely new solutions. That’s why we chose an interactive, cohort-based format for Elephant AI, instead of a traditional course based solely on video content.
6 weeks full of knowledge, case studies, and community interaction
Today, understanding AI largely depends on how well the context is explained. During the Elephant AI course, we’ll share our best tactics — and there’s a good chance that, together with the whole group of participants, we’ll discover completely new solutions. That’s why we chose an interactive, cohort-based format for Elephant AI, instead of a traditional course based solely on video content.
6 weeks full of knowledge, case studies, and community interaction
Today, understanding AI largely depends on how well the context is explained. During the Elephant AI course, we’ll share our best tactics — and there’s a good chance that, together with the whole group of participants, we’ll discover completely new solutions. That’s why we chose an interactive, cohort-based format for Elephant AI, instead of a traditional course based solely on video content.
6 weeks full of knowledge, case studies, and community interaction
Today, understanding AI largely depends on how well the context is explained. During the Elephant AI course, we’ll share our best tactics — and there’s a good chance that, together with the whole group of participants, we’ll discover completely new solutions. That’s why we chose an interactive, cohort-based format for Elephant AI, instead of a traditional course based solely on video content.
This isn’t just a three-hour session, a quick certificate you post on LinkedIn, and that’s it. Here, it really feels more like an MBA program — you have to put in the work, because it’s not easy, but what you learn stays with you for a long time.
~
Cezary Orzechowski
IT Project Manager
This isn’t just a three-hour session, a quick certificate you post on LinkedIn, and that’s it. Here, it really feels more like an MBA program — you have to put in the work, because it’s not easy, but what you learn stays with you for a long time.
~
Cezary Orzechowski
IT Project Manager
This isn’t just a three-hour session, a quick certificate you post on LinkedIn, and that’s it. Here, it really feels more like an MBA program — you have to put in the work, because it’s not easy, but what you learn stays with you for a long time.
~
Cezary Orzechowski
IT Project Manager
This isn’t just a three-hour session, a quick certificate you post on LinkedIn, and that’s it. Here, it really feels more like an MBA program — you have to put in the work, because it’s not easy, but what you learn stays with you for a long time.
~
Cezary Orzechowski
IT Project Manager
Course agenda
Module
1
Introduction to Generative AI
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, image
Results
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Module
1
Introduction to Generative AI
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, image
Results
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Module
1
Introduction to Generative AI
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Module
1
Introduction to Generative AI
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Topics
Introduction to foundational models and terminology
Genealogy and timeline of LLMs (with applications)
Examples of use: chat, image, music
Open vs closed source
Prompt engineering – text, imageResults
You can explain key concepts and terminology related to generative AI and foundational models
You understand the development stages of large language models (LLMs), their genealogy, and you can name real-world use cases
You can compare and evaluate open-source vs commercial generative AI models
You can apply prompt engineering techniques in practical text and image-based scenarios
You can identify and assess the potential uses of generative AI across different domains, such as chatbots, image generation, or music
Projects
Creating prompts for text-based models
Creating prompts for image-based models
Choosing the right model for a given task
Module
2
GenAI – image
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Module
2
GenAI – image
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Module
2
GenAI – image
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Module
2
GenAI – image
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Topics
How diffusion models work
Building prompts step by step
Your own app: Gradio + Stable Diffusion
Fine-tuning Stable Diffusion (Dreambooth)
Results
You understand how diffusion models work and can explain their core principles in the context of generative AI
You create and refine image generation prompts step by step, demonstrating your understanding of process and technique
You use tools like Gradio and Streamlit to share and test generative models
You work with DALL·E 3 via OpenAI's GUI and API, showing your ability to integrate and apply these tools in practical use cases
You can fine-tune Stable Diffusion (SD) using techniques like Dreambooth to create personalized, targeted content
Projects
Synthetic models: creating visualizations with virtual models of any gender, skin tone, or body type
Interior design: styling spaces from text descriptions, modifying layouts based on client prompts
Automating graphic generation for marketing campaigns and more
Module
3
GenAI – text
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Module
3
GenAI – text
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Module
3
GenAI – text
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Module
3
GenAI – text
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Topics
Transformer: origin – a short intro to LLM architecture and how it works
Use case 1: Text generation with LLM, summarization
Use case 2: Q&A with LLM, HF assistant
Use case 3: Fine-tuning a language model
Results
You understand the core principles of Transformer architecture and its importance in the context of large language models (LLMs)
You apply LLMs to generate text and summaries, showing the ability to configure and run such models
You use LLMs for Q&A tasks and assistant functionalities, demonstrating integration and practical implementation skills
You can fine-tune a language model for custom content — both personal and private
Projects
Building a tool for automatically summarizing long documents — especially useful for audits, complaint analysis, legal texts, and client correspondence
Automating writing tasks: posts, ads, emails personalized to customer needs
Generating educational materials and training scenarios for internal use
Module
4
GenAI – audio
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Module
4
GenAI – audio
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Module
4
GenAI – audio
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Module
4
GenAI – audio
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Topics
How GenAI models for sound / voice / music work
Use case 1: Audiocraft
Use case 2: Bark/Suno – voice cloning
Use case 3: TTS – Parler
Results
You can explain how generative models for sound, voice, and music work, including the core principles and techniques used in these models
You apply Audiocraft to generate music, demonstrating the ability to create original compositions using generative models
You use tools like Bark/Suno for voice cloning, showing the ability to produce realistic voice replicas
You use Text-to-Speech (TTS) technologies via tools like Parler, demonstrating your ability to convert text into natural-sounding speech
You tailor generative models for specific audio and music-related tasks, showing your ability to personalize and optimize models for desired outcomes
Projects
Designing a solution based on AI Agents
Module
5
GenAI – video
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Module
5
GenAI – video
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Module
5
GenAI – video
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Module
5
GenAI – video
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Topics
How generative video models work
Use case 1: text → video
Use case 2: image → video
Use case 3: video → video (style transfer)
Results
You can explain how generative video models work, describing the basic principles and techniques used to generate and modify video content
You use generative models to create videos based on text input (text-to-video)
You transform images into videos (image-to-video) using generative models, showing your ability to create dynamic visuals from static images
You can apply video-to-video style transfer techniques
You are able to fine-tune generative video models for specific tasks, showing skill in model personalization and optimization to achieve desired visual effects
Projects
Video style transfer for marketing campaigns
Automatic video generation with product demonstrations
Interior design: virtual 3D environments showcasing designers' work
Module
6
GenAI – multimodal
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Module
6
GenAI – multimodal
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Module
6
GenAI – multimodal
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Module
6
GenAI – multimodal
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Topics
Combining solutions across domains: text, image, video, audio
Use case 1: image-to-text
Use case 2: video-to-text
Use case 3: text-to-speech
Use case 4: image transcription
Use case 5: presentation generation
Results
You can explain how to combine generative technologies across multiple domains (text, image, video, audio) to create advanced multimodal applications
You use image-to-text technology to transform images into descriptive captions using generative models
You apply video-to-text technology to generate text descriptions based on video content, showing your ability to analyze and synthesize visual information into language
You use text-to-speech technology to turn written content into natural-sounding speech, demonstrating your ability to work with speech synthesis models
You can integrate multiple generative tools to build advanced applications like a voice assistant with summarization features, showing your skills in building complex multimodal AI systems
Projects
Creating try-on apps that show how clothing would fit on a specific person
Developing avatars that speak in your voice and look like you
Generating complete PowerPoint presentations based on user input and guidelines
Module
7
+
Module
8
RAG
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Module
7
+
Module
8
RAG
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Module
7
+
Module
8
RAG
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Module
7
+
Module
8
RAG
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Topics
Problems with LLMs: hallucinations, outdated knowledge
RAG: key components
Introduction to vector databases
Results
You identify and explain key issues related to large language models (LLMs), such as hallucinations or outdated knowledge
You can describe and understand the core components of Retrieval-Augmented Generation (RAG) and its role in improving the accuracy and freshness of generated outputs
You know the basics of vector databases and their use in the context of RAG
You build a basic RAG system, showing your ability to integrate technologies to improve LLM performance
Projects
An intelligent chatbot that answers client questions with company-specific data, in a secure way
An internal chatbot acting as a knowledge base for employees (e.g. procedures, processes, templates)
HR document automation: job descriptions, evaluation forms, development plans
Module
9
Evaluation
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Module
9
Evaluation
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Module
9
Evaluation
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Module
9
Evaluation
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Topics
How to measure what LLMs produce: metric overview
Use case 1: DeepEval
Use case 2: Promptbench
Use case 3: Giskard
Results
You identify and explain different metrics used to evaluate LLM performance
You apply DeepEval to assess LLM effectiveness
You use Promptbench to compare prompts and analyze their influence on model outputs
You perform model evaluations using Giskard
You independently evaluate fine-tuned models using the skills and tools you've acquired
Projects
Evaluating the quality of generated content: text, image, multimodal
Choosing the right metrics for different use cases
Module
10
Monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Module
10
Monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Module
10
Monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Module
10
Monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Topics
Are LLMs doing what they’re supposed to? How to avoid becoming Tay 2.0
Use case 1: Llama Guard
Use case 2: Fiddler
Use case 3: Arize Phoenix
Results
You understand and can explain the importance of monitoring large language models (LLMs) to ensure they behave as expected and don’t generate harmful content
You can apply Llama Guard to monitor and control LLMs
You use Fiddler to monitor model performance in real time, analyze results, and adjust models to improve performance
You conduct LLM monitoring using Arize Phoenix, demonstrating your ability to detect, diagnose, and resolve issues in generative models
You independently monitor fine-tuned models, applying your skills and tools to ensure alignment with expectations and avoid failures like Tay 2.0
Projects
Model behavior analysis: safety and speed
Using automated tools to scale GenAI model monitoring
Expand your portfolio with the following technologies:
GPT4
(
text
)
GPT4
GPT4
(
text
)
LlamaIndex
(
RAG
)
LlamaIndex
LlamaIndex
(
RAG
)
Stable Diffusion
(
images
)
Stable Diffusion
Stable Diffusion
(
images
)
Janus-Pro
(
images
)
Janus-Pro
Janus-Pro
(
images
)
DeepSeek
(
text
)
DeepSeek
DeepSeek
(
text
)
Dall-E
(
images
)
Dall-E
Dall-E
(
images
)
LangChain
(
RAG
)
LangChain
LangChain
(
RAG
)
Flux
(
images
)
Flux
Flux
(
images
)
Whisper
(
audio
)
Whisper
Whisper
(
audio
)
PromptBench
(
evaluation
)
PromptBench
PromptBench
(
evaluation
)
Llava
(
multimodal
)
Llava
Llava
(
multimodal
)
Bark
(
audio
)
Bark
Bark
(
audio
)
Arize
(
monitoring
)
Arize
Arize
(
monitoring
)
Llama 3
(
text
)
Llama 3
Llama 3
(
text
)
Audiocraft
(
audio
)
Audiocraft
Audiocraft
(
audio
)
Idefix2
(
multimodal
)
Idefix2
Idefix2
(
multimodal
)
Gemma
(
text
)
Gemma
Gemma
(
text
)
Fiddler
(
monitoring
)
Fiddler
Fiddler
(
monitoring
)
What I like most about the course is that it’s non-technical. You don’t need a technical background to understand what’s going on. The course also nudged me in a new direction. Until now, I had been focused mainly on content creation and writing, but now I feel the need to change something. I’ve already read two or three books on Data Science, started a beginner’s Python course, and I’m thinking about what else I could explore to keep growing. On a personal level, that’s the greatest value the course has given me.
~
Maciej Drabik
Embedded Writer for IT
What I like most about the course is that it’s non-technical. You don’t need a technical background to understand what’s going on. The course also nudged me in a new direction. Until now, I had been focused mainly on content creation and writing, but now I feel the need to change something. I’ve already read two or three books on Data Science, started a beginner’s Python course, and I’m thinking about what else I could explore to keep growing. On a personal level, that’s the greatest value the course has given me.
~
Maciej Drabik
Embedded Writer for IT
What I like most about the course is that it’s non-technical. You don’t need a technical background to understand what’s going on. The course also nudged me in a new direction. Until now, I had been focused mainly on content creation and writing, but now I feel the need to change something. I’ve already read two or three books on Data Science, started a beginner’s Python course, and I’m thinking about what else I could explore to keep growing. On a personal level, that’s the greatest value the course has given me.
~
Maciej Drabik
Embedded Writer for IT
What I like most about the course is that it’s non-technical. You don’t need a technical background to understand what’s going on. The course also nudged me in a new direction. Until now, I had been focused mainly on content creation and writing, but now I feel the need to change something. I’ve already read two or three books on Data Science, started a beginner’s Python course, and I’m thinking about what else I could explore to keep growing. On a personal level, that’s the greatest value the course has given me.
~
Maciej Drabik
Embedded Writer for IT
Who will be teaching you
Instructor of the course
Konrad Banachewicz, PhD
Kaggle Grandmaster and a distinguished expert in the field of AI, Konrad is one of the most versatile and experienced professionals in the industry. He began his journey with AI over 20 years ago.
After earning his PhD from Vrije Universiteit in Amsterdam, where he focused on research into modeling extreme dependencies in credit risk, he began applying his skills to practical business problems.
Konrad has worked with prestigious financial institutions such as ABN AMRO, RBS, and ING, building machine learning solutions to solve key investment challenges. In 2015, he was invited to create the central data science team at eBay Classifieds Group. He currently works at IKEA AI Lab in Amsterdam as a Principal Data Scientist.
He has gone through all stages of the data product lifecycle — from understanding business requirements, through data acquisition and preprocessing, modeling, testing, and deployment, to presenting results to executive stakeholders.
Konrad has an impressive track record of building AI solutions across various industries — including high frequency trading, credit risk, agricultural yield forecasting, anomaly detection in industrial systems, recommendation optimization, and multimedia shopping assistants. His work in AI has been groundbreaking, especially in times when most businesses still viewed AI as a curiosity.
He’s passionate about knowledge sharing and mentoring young talent. A bestselling author of books on AI, he believes that the key to success lies not just in the ability to solve real-world problems, but also in understanding how to avoid common mistakes.
Outside of work, Konrad is an active participant in Kaggle competitions and trains in Krav Maga. He is someone who continuously strives for improvement — both professionally and personally.
Who will be teaching you
Instructor of the course
Konrad Banachewicz, PhD
Kaggle Grandmaster and a distinguished expert in the field of AI, Konrad is one of the most versatile and experienced professionals in the industry. He began his journey with AI over 20 years ago.
After earning his PhD from Vrije Universiteit in Amsterdam, where he focused on research into modeling extreme dependencies in credit risk, he began applying his skills to practical business problems.
Konrad has worked with prestigious financial institutions such as ABN AMRO, RBS, and ING, building machine learning solutions to solve key investment challenges. In 2015, he was invited to create the central data science team at eBay Classifieds Group. He currently works at IKEA AI Lab in Amsterdam as a Principal Data Scientist.
He has gone through all stages of the data product lifecycle — from understanding business requirements, through data acquisition and preprocessing, modeling, testing, and deployment, to presenting results to executive stakeholders.
Konrad has an impressive track record of building AI solutions across various industries — including high frequency trading, credit risk, agricultural yield forecasting, anomaly detection in industrial systems, recommendation optimization, and multimedia shopping assistants. His work in AI has been groundbreaking, especially in times when most businesses still viewed AI as a curiosity.
He’s passionate about knowledge sharing and mentoring young talent. A bestselling author of books on AI, he believes that the key to success lies not just in the ability to solve real-world problems, but also in understanding how to avoid common mistakes.
Outside of work, Konrad is an active participant in Kaggle competitions and trains in Krav Maga. He is someone who continuously strives for improvement — both professionally and personally.
Who will be teaching you
Instructor of the course
Konrad Banachewicz, PhD
Kaggle Grandmaster and a distinguished expert in the field of AI, Konrad is one of the most versatile and experienced professionals in the industry. He began his journey with AI over 20 years ago.
After earning his PhD from Vrije Universiteit in Amsterdam, where he focused on research into modeling extreme dependencies in credit risk, he began applying his skills to practical business problems.
Konrad has worked with prestigious financial institutions such as ABN AMRO, RBS, and ING, building machine learning solutions to solve key investment challenges. In 2015, he was invited to create the central data science team at eBay Classifieds Group. He currently works at IKEA AI Lab in Amsterdam as a Principal Data Scientist.
He has gone through all stages of the data product lifecycle — from understanding business requirements, through data acquisition and preprocessing, modeling, testing, and deployment, to presenting results to executive stakeholders.
Konrad has an impressive track record of building AI solutions across various industries — including high frequency trading, credit risk, agricultural yield forecasting, anomaly detection in industrial systems, recommendation optimization, and multimedia shopping assistants. His work in AI has been groundbreaking, especially in times when most businesses still viewed AI as a curiosity.
He’s passionate about knowledge sharing and mentoring young talent. A bestselling author of books on AI, he believes that the key to success lies not just in the ability to solve real-world problems, but also in understanding how to avoid common mistakes.
Outside of work, Konrad is an active participant in Kaggle competitions and trains in Krav Maga. He is someone who continuously strives for improvement — both professionally and personally.
Who will be teaching you
Instructor of the course
Konrad Banachewicz, PhD
Kaggle Grandmaster and a distinguished expert in the field of AI, Konrad is one of the most versatile and experienced professionals in the industry. He began his journey with AI over 20 years ago.
After earning his PhD from Vrije Universiteit in Amsterdam, where he focused on research into modeling extreme dependencies in credit risk, he began applying his skills to practical business problems.
Konrad has worked with prestigious financial institutions such as ABN AMRO, RBS, and ING, building machine learning solutions to solve key investment challenges. In 2015, he was invited to create the central data science team at eBay Classifieds Group. He currently works at IKEA AI Lab in Amsterdam as a Principal Data Scientist.
He has gone through all stages of the data product lifecycle — from understanding business requirements, through data acquisition and preprocessing, modeling, testing, and deployment, to presenting results to executive stakeholders.
Konrad has an impressive track record of building AI solutions across various industries — including high frequency trading, credit risk, agricultural yield forecasting, anomaly detection in industrial systems, recommendation optimization, and multimedia shopping assistants. His work in AI has been groundbreaking, especially in times when most businesses still viewed AI as a curiosity.
He’s passionate about knowledge sharing and mentoring young talent. A bestselling author of books on AI, he believes that the key to success lies not just in the ability to solve real-world problems, but also in understanding how to avoid common mistakes.
Outside of work, Konrad is an active participant in Kaggle competitions and trains in Krav Maga. He is someone who continuously strives for improvement — both professionally and personally.
Special guests
Luca Massaron
Data Science & Modelling Senior Expert at illimity Bank | MBA | Book Author @ Wiley, Packt, Manning | 3x Kaggle Grandmaster | GDE in AI and Machine Learning
Maria Parysz
CEO and Owner at ElephantAI, LogicAI & RecoAI
Luca Massaron
Data Science & Modelling Senior Expert at illimity Bank | MBA | Book Author @ Wiley, Packt, Manning | 3x Kaggle Grandmaster | GDE in AI and Machine Learning
Maria Parysz
CEO and Owner at ElephantAI, LogicAI & RecoAI
Luca Massaron
Data Science & Modelling Senior Expert at illimity Bank | MBA | Book Author @ Wiley, Packt, Manning | 3x Kaggle Grandmaster | GDE in AI and Machine Learning
Maria Parysz
CEO and Owner at ElephantAI, LogicAI & RecoAI
Luca Massaron
Data Science & Modelling Senior Expert at illimity Bank | MBA | Book Author @ Wiley, Packt, Manning | 3x Kaggle Grandmaster | GDE in AI and Machine Learning
Maria Parysz
CEO and Owner at ElephantAI, LogicAI & RecoAI
The course fills an important gap between the world of data scientists and the world of business, creating a natural bridge between the two. I really appreciate the opportunity to organize the knowledge I already had. Before, it was often fragmented and taken out of a broader context. Now, it’s starting to form a logical and coherent whole.
~
Paweł Koziołek
AI Marketer / Keen on fancy buzzwords of Data Science & ML / 1. Focus, 2. Achiever, 3. Competition, 4. Strategic, 5. Command
The course fills an important gap between the world of data scientists and the world of business, creating a natural bridge between the two. I really appreciate the opportunity to organize the knowledge I already had. Before, it was often fragmented and taken out of a broader context. Now, it’s starting to form a logical and coherent whole.
~
Paweł Koziołek
AI Marketer / Keen on fancy buzzwords of Data Science & ML / 1. Focus, 2. Achiever, 3. Competition, 4. Strategic, 5. Command
The course fills an important gap between the world of data scientists and the world of business, creating a natural bridge between the two. I really appreciate the opportunity to organize the knowledge I already had. Before, it was often fragmented and taken out of a broader context. Now, it’s starting to form a logical and coherent whole.
~
Paweł Koziołek
AI Marketer / Keen on fancy buzzwords of Data Science & ML / 1. Focus, 2. Achiever, 3. Competition, 4. Strategic, 5. Command
The course fills an important gap between the world of data scientists and the world of business, creating a natural bridge between the two. I really appreciate the opportunity to organize the knowledge I already had. Before, it was often fragmented and taken out of a broader context. Now, it’s starting to form a logical and coherent whole.
~
Paweł Koziołek
AI Marketer / Keen on fancy buzzwords of Data Science & ML / 1. Focus, 2. Achiever, 3. Competition, 4. Strategic, 5. Command
What our clients say about us
Seweryn Rogut
3D Point cloud data | Photogrammetry | Project manager | AI Enthusiast
GenAI™ + AI Agents – completed! 🤖💡
Over the past 12 weeks, I took part in two intensive courses organized by Elephant AI and led by Konrad Banachewicz and Maria Parysz. These trainings were not only an opportunity to gain new knowledge, but also to apply artificial intelligence in real, practical ways.
During the courses, I learned how to:
➡️ Fine-tune language models (LLMs) – allowing for the adaptation of large models to specific business needs and use cases.
➡️ Use RAG techniques (Retrieval-Augmented Generation) – effectively combining LLMs with external data sources to provide precise, context-aware responses.
➡️ Build advanced multi-agent solutions – enabling the automation of complex processes through intelligent agents collaborating on dedicated tasks.
➡️ Implement and monitor AI in the cloud – essential skills for scaling AI projects and ensuring performance and reliability in production environments.
As my final project, I created an intelligent customer service assistant that automates purchase, complaint, and return processes—streamlining operations and improving the customer experience. The project was recognized with a Best Practical Application badge – nothing huge, but it definitely made me smile 😁.
The time I spent with Elephant AI was not only inspiring but also full of challenges and rewarding moments. These courses helped me expand my AI skill set and gain valuable hands-on experience.
Benjamin Kadzioch
Project Manager | Program Manager | AI Consultant | GenAI | AI Agents | Native German
I am excited to share that I have received a new certificate 𝗚𝗲𝗻𝗔𝗜 𝗖𝗼𝗱𝗲 from Elephant AI! These were 6 weeks of intensive coding experience confirmed by a final capstone coding project: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗔𝗜 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝘀𝘄𝗲𝗿𝗶𝗻𝗴 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗮𝗯𝗼𝘂𝘁 𝗪𝗵𝗶𝘀𝘁𝗹𝗲𝗯𝗹𝗼𝘄𝗲𝗿 𝗟𝗮𝘄 𝘂𝘀𝗶𝗻𝗴 𝗟𝗟𝗠 𝗮𝗻𝗱 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲.
During the course I have learned how to work with:
🐍 𝗣𝘆𝘁𝗵𝗼𝗻 (using libraries like Transformers, PyTorch, OpenCV, Fitz/PyMuPDF, LangChain etc.)
🔤 𝗧𝗲𝘅𝘁:
Building Assistants and Chatbots via API or using Open-Source LLM’s executed locally or with use of GPU
LLM Fine-Tuning
🏙 𝗜𝗺𝗮𝗴𝗲:
Generation and Edition using Open-Source Models (e.g. Stable Diffusion)
Fine-Tuning with own images
Use of User Interfaces (UI) for Proof of Concept (PoC) purposes
🔈 𝗩𝗼𝗶𝗰𝗲/𝗔𝘂𝗱𝗶𝗼:
Voice transcription
Text-to-speech
Music/Audio generation
Building Voice Assistants
📽 𝗩𝗶𝗱𝗲𝗼:
Text-to-video
Image-to-video
Video-to-video
Transcription and summary of videos with translation and speech generation
🤖 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀:
Describing images (based on VLM - Vision Language Models)
Converting text images into editable formats (OCR)
Extracting information from video in order to generate video description or voiceover script
Slide narration based on PowerPoint presentations
🗃 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲:
Uploading own documents and extracting information from PDF, Excel, Word etc. (e.g. LllamaIndex)
Use of Vector Databases (e.g. Chroma)
Use of Knowledge Graphs (e.g. GraphRAG)
Multimodal RAG
🎯 𝗟𝗟𝗠 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 (e.g. DeepEval, Giskard, Ragas):
Answer Relevancy
Faithfulness
Contextual Precision
Contextual Recall
Hallucinations
Bias
Toxicity
📊 𝗟𝗟𝗠 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 (e.g. Llama Guard, Prompt Guard, LangKit):
Safety
Prompt Injection
Jailbreaks
👏 Many thanks to Konrad Banachewicz for transferring knowledge in such a wonderful way!
🚀 Next stop: Building 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀!
Piotr Kochanek
Designer at Asseco Poland S.A.
I’m happy to share that I’ve completed the GenAI Code course organized by Elephant AI! 🎓 I gained hands-on skills in working with generative AI across text, audio, video, and image, including text-to-speech and speech-to-text conversion. A major focus was on integrating models with various data sources (RAG), allowing for relevant and up-to-date responses. I also learned techniques for fine-tuning models and deploying them in cloud environments.
During the course, I explored both the potential and the limitations of AI. It’s a fascinating technology with huge possibilities—though its inner workings often reveal a lack of true intelligence. I realized how important it is to evaluate whether a model generates trustworthy outputs, and to monitor its use to prevent misuse—like malicious prompts or inappropriate content generation.
AI development brings both opportunities and challenges. On the one hand, it can support us in daily tasks such as automation and education (where it clearly shows great promise). On the other hand, it raises questions about ethics, the future of the job market, and the need for global regulations (though who exactly would enforce those?..).
Thank you to the course organizers at Elephant AI, and especially to instructor Konrad Banachewicz, for such an intense and well-rounded program. Despite my prior experience with AI, this course gave me a much more complete picture—from practical tools to the less obvious aspects I hadn’t considered before. The knowledge I gained has significantly expanded my skill set and opened up new perspectives in working with AI.
Konrad Juszczuk
Digital Transformation | Controlling Solutions | AI | Business Analyst | Financial Controller
Thrilled to share that I’ve just completed the ‘GenAI Code’ course, a deep dive into the world of AI, skillfully orchestrated by Konrad Banachewicz and offered by Elephant AI.
As always, Konrad Banachewicz managed to make the complex look easy—guess that’s just another day at the office for us coding enthusiasts! Excited to apply these new skills in my work. A huge thank you to the Elephant AI team and Konrad for the knowledge and the fun journey. Here’s to many more lines of code and fewer bugs in our future! 🚀
Kamil Winiarski
Senior Technical Support Specialist | AI Enthusiast | Exploring the Future of Machine Learning and Automation | Thinker. Innovator. AI Explorer | Cybersecurity
🤖 I'm excited to share that I’ve earned the Elephant AI – GenAI Code certificate from Elephant AI!
I’m grateful for the opportunity to grow and for reaching this milestone.
Over 6 intense weeks, I gained knowledge in the following areas:
🔹 Applying AI and large language models (𝗟𝗟𝗠s) to various modalities such as text, image, audio, and video
🔹 Coding useful solutions in 𝗣𝘆𝘁𝗵𝗼𝗻, including chatbots and image generators
🔹 Fine-tuning LLMs and using Retrieval-Augmented Generation (𝗥𝗔𝗚) to produce more accurate text outputs
🔹 Implementing, evaluating, and monitoring 𝗚𝗲𝗻𝗔𝗜 solutions based on LLMs, and deploying them in cloud environments
To complete the course, I had to pass all 10 module assessments and succeed in a Kaggle challenge. During the final task, I built a script capable of solving a specific problem—an experience that truly tested and validated what I’d learned.
Ariel Zgórski
IT Area Lead ➤ AI & Generative AI🔹Data Science🔹Cloud Solutions🔹Python🔹Project & Program Management🔹Backend Solutions🔹IoT / Smart Home / Smart City🔹ESG / Electromobility🔹VR & AR
Excellent preparation and delivery by Konrad Banachewicz! 👏 Even though this was a coding course—and a demanding one—Konrad managed to run it in such a way that even someone as far from programming as I am could get a feel for what it means to use LLMs via API, generate images with Stable Diffusion, or build RAG systems. 🚀
This is yet another course I’ve taken thanks to Maria Parysz, and I always make a point of highlighting that. 🙌 Maria and her courses are truly professional level, and this course only reinforces that! 🥇
Dominik Dobry
Scrum Master in STS GG and Agile leadership apprentice
I’m not a programmer, and I’m not planning to become one—but this certificate holds special meaning for me for several reasons:
➡ Self-recognition – In a world where expectations are constantly growing, 6 weeks of intense work, learning, and challenges is something worth celebrating.
➡ Reflection on the role of a Scrum Master and Agile Coach – These roles are often reduced to simple labels: “meeting organizer,” “consultant,” or “Scrum enforcer.” In reality, the people I know in these roles—myself included—are on the front lines of organizational change. As first adopters and first followers, we don’t just support transformations; we help inspire and shape new directions. This certificate is proof that continuous growth is possible, even in a fast-changing world.
➡ Gratitude to the Elephant AI community – Maria Parysz and Konrad Banachewicz are doing something incredible by creating a space for education and growth in the GenAI space. Thanks to them, the community feels like a peloton—encouraging, supportive, and helping everyone catch up with the rapid pace of technology. Without their open and inclusive approach, this certificate wouldn’t have been possible.
To me, this certificate doesn’t mean I’ll start coding—but it does give me the tools to:
better understand the potential of GenAI,
inspire more technical people to take action,
and support teams and organizations in building future-ready environments.
Grzegorz Józefiak
IT Project manager, AI Manager
I’ve completed the 6-week GenAI Code course organized by Elephant AI! 🎉 And it was a perfect choice. Huge thanks to Konrad Banachewicz for the substance, the calm analytical approach, the sense of humor with just the right edge—and for an absolutely fascinating journey through the world of Generative AI.
The technology we now call AI carries immense power, offering both opportunities and risks that need to be felt and understood. Experiencing the differences between local and cloud processing environments, open-source models and those accessed via API, and going from mono- and multimodal models through RAG, evaluation, and solution monitoring—that’s the foundation I needed to have… and now I do.
For someone like me, whose journey with software, systems, and machines began back when computers existed only in large computing centers, this was another step in staying up to date with technology. Six weeks in theory, but in practice it was months of intense analysis and case studies to build my own environment—a space where I can continue experimenting so that the AI-driven components in the projects I manage deliver real business value.
Many thanks—and now I’m diving into “AI Agents Solutions for the Future”, continuing the journey with Elephant AI.
Justyna Karaś
Executive MBA | PMP | SAP | Digital Transformation Leader | Master Black Belt
🌟 Thrilled to share that I’ve successfully completed the GenAI Code course by Elephant AI! 🎉
Over the past six weeks, I’ve gained invaluable hands-on experience in:
🔹 Utilizing AI and large language models (LLMs) for tasks across text, images, audio, and video.
🔹 Developing practical Python solutions, including chatbots and image generators.
🔹 Fine-tuning LLMs and applying Retrieval-Augmented Generation (RAG) techniques.
The course concluded with completing 10 module assessments and participating in a Kaggle competition, where I applied my knowledge to tackle a real-world challenge.
Excited to continue my AI learning journey with the AI Agents: Tools of the Future course! 😎
A big thank you to Konrad Banachewicz, Maria Parysz, and the incredible Elephant AI community for their guidance and inspiration throughout this journey!
Maciej Wnuk
Compliance, anti-corruption, whistleblowers, ethics – well-received trainings, effective implementations
📕 If you’re not expanding your knowledge, you’re falling behind!
📕 I’m proud to share that I’ve completed the intensive GenAI Code course, led by Konrad Banachewicz and organized by Elephant AI.
📕 Throughout the course, of course, we had to complete mandatory homework assignments—and finish with a final project.
📕 Mr. Konrad shared an incredible amount of theoretical knowledge and its practical applications—plenty of material to reflect on and continue exploring for months to come.
📕 Getting a peek behind the curtain of artificial intelligence and experimenting with its more advanced uses on my own was a fantastic adventure.
🍎 Especially considering how fast AI is entering our professional lives—faster than personal computers did back in the day.
Damian Augustyn
Product Manager | +5 years in tech | AI practitioner | PMI-ACP | PSPO II
I’m happy to share that I’ve completed the GenAI Code certification from Elephant AI!
TL;DR – what you can take away from this course:
Working with all kinds of multimodal models, combining them, and implementing directly in code.
Prompt engineering
Model fine-tuning using LoRA (example in the photo: using a fine-tuned FLUX model on my own images)
RAG using various document types: pdf, img, csv, xls.
Evaluating and refining RAG-based implementations, verifying answer accuracy metrics.
Big congrats and thanks to Konrad Banachewicz – you set a demanding pace, but thanks to that, the level of “substance” in this course was truly high! Well done!
Thanks also to Maria Parysz and Alex Kwiatkowski for organizing Elephant AI – you’re doing an amazing job!
What’s next? Agents 🤖
Bartosz Urban
Python | Data Analytics | GenAI | BI | AdTech
💡 A new chapter in my tech journey!
I’m thrilled to share that I’ve earned the Elephant AI – GenAI Code certificate from Elephant AI! It was 6 intense weeks of learning that helped me develop hands-on skills in the field of Generative AI.
During the course, I explored:
🔹 Coding GenAI-based solutions in Python, including chatbot and image generator development
🔹 Applying large language models (LLMs) across multiple modalities: text, images, audio, and video
🔹 Fine-tuning LLMs and using RAG (Retrieval-Augmented Generation) to generate more accurate results
🔹 Implementing, evaluating, and deploying GenAI solutions
I work with AI on a daily basis, and the knowledge I’ve gained will help me deliver even better results and develop innovative, AI-powered solutions. I can’t wait to put these skills into practice! 🚀
Seweryn Rogut
3D Point cloud data | Photogrammetry | Project manager | AI Enthusiast
GenAI™ + AI Agents – completed! 🤖💡
Over the past 12 weeks, I took part in two intensive courses organized by Elephant AI and led by Konrad Banachewicz and Maria Parysz. These trainings were not only an opportunity to gain new knowledge, but also to apply artificial intelligence in real, practical ways.
During the courses, I learned how to:
➡️ Fine-tune language models (LLMs) – allowing for the adaptation of large models to specific business needs and use cases.
➡️ Use RAG techniques (Retrieval-Augmented Generation) – effectively combining LLMs with external data sources to provide precise, context-aware responses.
➡️ Build advanced multi-agent solutions – enabling the automation of complex processes through intelligent agents collaborating on dedicated tasks.
➡️ Implement and monitor AI in the cloud – essential skills for scaling AI projects and ensuring performance and reliability in production environments.
As my final project, I created an intelligent customer service assistant that automates purchase, complaint, and return processes—streamlining operations and improving the customer experience. The project was recognized with a Best Practical Application badge – nothing huge, but it definitely made me smile 😁.
The time I spent with Elephant AI was not only inspiring but also full of challenges and rewarding moments. These courses helped me expand my AI skill set and gain valuable hands-on experience.
Kamil Winiarski
Senior Technical Support Specialist | AI Enthusiast | Exploring the Future of Machine Learning and Automation | Thinker. Innovator. AI Explorer | Cybersecurity
🤖 I'm excited to share that I’ve earned the Elephant AI – GenAI Code certificate from Elephant AI!
I’m grateful for the opportunity to grow and for reaching this milestone.
Over 6 intense weeks, I gained knowledge in the following areas:
🔹 Applying AI and large language models (𝗟𝗟𝗠s) to various modalities such as text, image, audio, and video
🔹 Coding useful solutions in 𝗣𝘆𝘁𝗵𝗼𝗻, including chatbots and image generators
🔹 Fine-tuning LLMs and using Retrieval-Augmented Generation (𝗥𝗔𝗚) to produce more accurate text outputs
🔹 Implementing, evaluating, and monitoring 𝗚𝗲𝗻𝗔𝗜 solutions based on LLMs, and deploying them in cloud environments
To complete the course, I had to pass all 10 module assessments and succeed in a Kaggle challenge. During the final task, I built a script capable of solving a specific problem—an experience that truly tested and validated what I’d learned.
Justyna Karaś
Executive MBA | PMP | SAP | Digital Transformation Leader | Master Black Belt
🌟 Thrilled to share that I’ve successfully completed the GenAI Code course by Elephant AI! 🎉
Over the past six weeks, I’ve gained invaluable hands-on experience in:
🔹 Utilizing AI and large language models (LLMs) for tasks across text, images, audio, and video.
🔹 Developing practical Python solutions, including chatbots and image generators.
🔹 Fine-tuning LLMs and applying Retrieval-Augmented Generation (RAG) techniques.
The course concluded with completing 10 module assessments and participating in a Kaggle competition, where I applied my knowledge to tackle a real-world challenge.
Excited to continue my AI learning journey with the AI Agents: Tools of the Future course! 😎
A big thank you to Konrad Banachewicz, Maria Parysz, and the incredible Elephant AI community for their guidance and inspiration throughout this journey!
Benjamin Kadzioch
Project Manager | Program Manager | AI Consultant | GenAI | AI Agents | Native German
I am excited to share that I have received a new certificate 𝗚𝗲𝗻𝗔𝗜 𝗖𝗼𝗱𝗲 from Elephant AI! These were 6 weeks of intensive coding experience confirmed by a final capstone coding project: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗔𝗜 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝘀𝘄𝗲𝗿𝗶𝗻𝗴 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗮𝗯𝗼𝘂𝘁 𝗪𝗵𝗶𝘀𝘁𝗹𝗲𝗯𝗹𝗼𝘄𝗲𝗿 𝗟𝗮𝘄 𝘂𝘀𝗶𝗻𝗴 𝗟𝗟𝗠 𝗮𝗻𝗱 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲.
During the course I have learned how to work with:
🐍 𝗣𝘆𝘁𝗵𝗼𝗻 (using libraries like Transformers, PyTorch, OpenCV, Fitz/PyMuPDF, LangChain etc.)
🔤 𝗧𝗲𝘅𝘁:
Building Assistants and Chatbots via API or using Open-Source LLM’s executed locally or with use of GPU
LLM Fine-Tuning
🏙 𝗜𝗺𝗮𝗴𝗲:
Generation and Edition using Open-Source Models (e.g. Stable Diffusion)
Fine-Tuning with own images
Use of User Interfaces (UI) for Proof of Concept (PoC) purposes
🔈 𝗩𝗼𝗶𝗰𝗲/𝗔𝘂𝗱𝗶𝗼:
Voice transcription
Text-to-speech
Music/Audio generation
Building Voice Assistants
📽 𝗩𝗶𝗱𝗲𝗼:
Text-to-video
Image-to-video
Video-to-video
Transcription and summary of videos with translation and speech generation
🤖 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀:
Describing images (based on VLM - Vision Language Models)
Converting text images into editable formats (OCR)
Extracting information from video in order to generate video description or voiceover script
Slide narration based on PowerPoint presentations
🗃 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲:
Uploading own documents and extracting information from PDF, Excel, Word etc. (e.g. LllamaIndex)
Use of Vector Databases (e.g. Chroma)
Use of Knowledge Graphs (e.g. GraphRAG)
Multimodal RAG
🎯 𝗟𝗟𝗠 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 (e.g. DeepEval, Giskard, Ragas):
Answer Relevancy
Faithfulness
Contextual Precision
Contextual Recall
Hallucinations
Bias
Toxicity
📊 𝗟𝗟𝗠 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 (e.g. Llama Guard, Prompt Guard, LangKit):
Safety
Prompt Injection
Jailbreaks
👏 Many thanks to Konrad Banachewicz for transferring knowledge in such a wonderful way!
🚀 Next stop: Building 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀!
Ariel Zgórski
IT Area Lead ➤ AI & Generative AI🔹Data Science🔹Cloud Solutions🔹Python🔹Project & Program Management🔹Backend Solutions🔹IoT / Smart Home / Smart City🔹ESG / Electromobility🔹VR & AR
Excellent preparation and delivery by Konrad Banachewicz! 👏 Even though this was a coding course—and a demanding one—Konrad managed to run it in such a way that even someone as far from programming as I am could get a feel for what it means to use LLMs via API, generate images with Stable Diffusion, or build RAG systems. 🚀
This is yet another course I’ve taken thanks to Maria Parysz, and I always make a point of highlighting that. 🙌 Maria and her courses are truly professional level, and this course only reinforces that! 🥇
Maciej Wnuk
Compliance, anti-corruption, whistleblowers, ethics – well-received trainings, effective implementations
📕 If you’re not expanding your knowledge, you’re falling behind!
📕 I’m proud to share that I’ve completed the intensive GenAI Code course, led by Konrad Banachewicz and organized by Elephant AI.
📕 Throughout the course, of course, we had to complete mandatory homework assignments—and finish with a final project.
📕 Mr. Konrad shared an incredible amount of theoretical knowledge and its practical applications—plenty of material to reflect on and continue exploring for months to come.
📕 Getting a peek behind the curtain of artificial intelligence and experimenting with its more advanced uses on my own was a fantastic adventure.
🍎 Especially considering how fast AI is entering our professional lives—faster than personal computers did back in the day.
Piotr Kochanek
Designer at Asseco Poland S.A.
I’m happy to share that I’ve completed the GenAI Code course organized by Elephant AI! 🎓 I gained hands-on skills in working with generative AI across text, audio, video, and image, including text-to-speech and speech-to-text conversion. A major focus was on integrating models with various data sources (RAG), allowing for relevant and up-to-date responses. I also learned techniques for fine-tuning models and deploying them in cloud environments.
During the course, I explored both the potential and the limitations of AI. It’s a fascinating technology with huge possibilities—though its inner workings often reveal a lack of true intelligence. I realized how important it is to evaluate whether a model generates trustworthy outputs, and to monitor its use to prevent misuse—like malicious prompts or inappropriate content generation.
AI development brings both opportunities and challenges. On the one hand, it can support us in daily tasks such as automation and education (where it clearly shows great promise). On the other hand, it raises questions about ethics, the future of the job market, and the need for global regulations (though who exactly would enforce those?..).
Thank you to the course organizers at Elephant AI, and especially to instructor Konrad Banachewicz, for such an intense and well-rounded program. Despite my prior experience with AI, this course gave me a much more complete picture—from practical tools to the less obvious aspects I hadn’t considered before. The knowledge I gained has significantly expanded my skill set and opened up new perspectives in working with AI.
Dominik Dobry
Scrum Master in STS GG and Agile leadership apprentice
I’m not a programmer, and I’m not planning to become one—but this certificate holds special meaning for me for several reasons:
➡ Self-recognition – In a world where expectations are constantly growing, 6 weeks of intense work, learning, and challenges is something worth celebrating.
➡ Reflection on the role of a Scrum Master and Agile Coach – These roles are often reduced to simple labels: “meeting organizer,” “consultant,” or “Scrum enforcer.” In reality, the people I know in these roles—myself included—are on the front lines of organizational change. As first adopters and first followers, we don’t just support transformations; we help inspire and shape new directions. This certificate is proof that continuous growth is possible, even in a fast-changing world.
➡ Gratitude to the Elephant AI community – Maria Parysz and Konrad Banachewicz are doing something incredible by creating a space for education and growth in the GenAI space. Thanks to them, the community feels like a peloton—encouraging, supportive, and helping everyone catch up with the rapid pace of technology. Without their open and inclusive approach, this certificate wouldn’t have been possible.
To me, this certificate doesn’t mean I’ll start coding—but it does give me the tools to:
better understand the potential of GenAI,
inspire more technical people to take action,
and support teams and organizations in building future-ready environments.
Damian Augustyn
Product Manager | +5 years in tech | AI practitioner | PMI-ACP | PSPO II
I’m happy to share that I’ve completed the GenAI Code certification from Elephant AI!
TL;DR – what you can take away from this course:
Working with all kinds of multimodal models, combining them, and implementing directly in code.
Prompt engineering
Model fine-tuning using LoRA (example in the photo: using a fine-tuned FLUX model on my own images)
RAG using various document types: pdf, img, csv, xls.
Evaluating and refining RAG-based implementations, verifying answer accuracy metrics.
Big congrats and thanks to Konrad Banachewicz – you set a demanding pace, but thanks to that, the level of “substance” in this course was truly high! Well done!
Thanks also to Maria Parysz and Alex Kwiatkowski for organizing Elephant AI – you’re doing an amazing job!
What’s next? Agents 🤖
Konrad Juszczuk
Digital Transformation | Controlling Solutions | AI | Business Analyst | Financial Controller
Thrilled to share that I’ve just completed the ‘GenAI Code’ course, a deep dive into the world of AI, skillfully orchestrated by Konrad Banachewicz and offered by Elephant AI.
As always, Konrad Banachewicz managed to make the complex look easy—guess that’s just another day at the office for us coding enthusiasts! Excited to apply these new skills in my work. A huge thank you to the Elephant AI team and Konrad for the knowledge and the fun journey. Here’s to many more lines of code and fewer bugs in our future! 🚀
Grzegorz Józefiak
IT Project manager, AI Manager
I’ve completed the 6-week GenAI Code course organized by Elephant AI! 🎉 And it was a perfect choice. Huge thanks to Konrad Banachewicz for the substance, the calm analytical approach, the sense of humor with just the right edge—and for an absolutely fascinating journey through the world of Generative AI.
The technology we now call AI carries immense power, offering both opportunities and risks that need to be felt and understood. Experiencing the differences between local and cloud processing environments, open-source models and those accessed via API, and going from mono- and multimodal models through RAG, evaluation, and solution monitoring—that’s the foundation I needed to have… and now I do.
For someone like me, whose journey with software, systems, and machines began back when computers existed only in large computing centers, this was another step in staying up to date with technology. Six weeks in theory, but in practice it was months of intense analysis and case studies to build my own environment—a space where I can continue experimenting so that the AI-driven components in the projects I manage deliver real business value.
Many thanks—and now I’m diving into “AI Agents Solutions for the Future”, continuing the journey with Elephant AI.
Bartosz Urban
Python | Data Analytics | GenAI | BI | AdTech
💡 A new chapter in my tech journey!
I’m thrilled to share that I’ve earned the Elephant AI – GenAI Code certificate from Elephant AI! It was 6 intense weeks of learning that helped me develop hands-on skills in the field of Generative AI.
During the course, I explored:
🔹 Coding GenAI-based solutions in Python, including chatbot and image generator development
🔹 Applying large language models (LLMs) across multiple modalities: text, images, audio, and video
🔹 Fine-tuning LLMs and using RAG (Retrieval-Augmented Generation) to generate more accurate results
🔹 Implementing, evaluating, and deploying GenAI solutions
I work with AI on a daily basis, and the knowledge I’ve gained will help me deliver even better results and develop innovative, AI-powered solutions. I can’t wait to put these skills into practice! 🚀
Seweryn Rogut
3D Point cloud data | Photogrammetry | Project manager | AI Enthusiast
GenAI™ + AI Agents – completed! 🤖💡
Over the past 12 weeks, I took part in two intensive courses organized by Elephant AI and led by Konrad Banachewicz and Maria Parysz. These trainings were not only an opportunity to gain new knowledge, but also to apply artificial intelligence in real, practical ways.
During the courses, I learned how to:
➡️ Fine-tune language models (LLMs) – allowing for the adaptation of large models to specific business needs and use cases.
➡️ Use RAG techniques (Retrieval-Augmented Generation) – effectively combining LLMs with external data sources to provide precise, context-aware responses.
➡️ Build advanced multi-agent solutions – enabling the automation of complex processes through intelligent agents collaborating on dedicated tasks.
➡️ Implement and monitor AI in the cloud – essential skills for scaling AI projects and ensuring performance and reliability in production environments.
As my final project, I created an intelligent customer service assistant that automates purchase, complaint, and return processes—streamlining operations and improving the customer experience. The project was recognized with a Best Practical Application badge – nothing huge, but it definitely made me smile 😁.
The time I spent with Elephant AI was not only inspiring but also full of challenges and rewarding moments. These courses helped me expand my AI skill set and gain valuable hands-on experience.
Justyna Karaś
Executive MBA | PMP | SAP | Digital Transformation Leader | Master Black Belt
🌟 Thrilled to share that I’ve successfully completed the GenAI Code course by Elephant AI! 🎉
Over the past six weeks, I’ve gained invaluable hands-on experience in:
🔹 Utilizing AI and large language models (LLMs) for tasks across text, images, audio, and video.
🔹 Developing practical Python solutions, including chatbots and image generators.
🔹 Fine-tuning LLMs and applying Retrieval-Augmented Generation (RAG) techniques.
The course concluded with completing 10 module assessments and participating in a Kaggle competition, where I applied my knowledge to tackle a real-world challenge.
Excited to continue my AI learning journey with the AI Agents: Tools of the Future course! 😎
A big thank you to Konrad Banachewicz, Maria Parysz, and the incredible Elephant AI community for their guidance and inspiration throughout this journey!
Ariel Zgórski
IT Area Lead ➤ AI & Generative AI🔹Data Science🔹Cloud Solutions🔹Python🔹Project & Program Management🔹Backend Solutions🔹IoT / Smart Home / Smart City🔹ESG / Electromobility🔹VR & AR
Excellent preparation and delivery by Konrad Banachewicz! 👏 Even though this was a coding course—and a demanding one—Konrad managed to run it in such a way that even someone as far from programming as I am could get a feel for what it means to use LLMs via API, generate images with Stable Diffusion, or build RAG systems. 🚀
This is yet another course I’ve taken thanks to Maria Parysz, and I always make a point of highlighting that. 🙌 Maria and her courses are truly professional level, and this course only reinforces that! 🥇
Piotr Kochanek
Designer at Asseco Poland S.A.
I’m happy to share that I’ve completed the GenAI Code course organized by Elephant AI! 🎓 I gained hands-on skills in working with generative AI across text, audio, video, and image, including text-to-speech and speech-to-text conversion. A major focus was on integrating models with various data sources (RAG), allowing for relevant and up-to-date responses. I also learned techniques for fine-tuning models and deploying them in cloud environments.
During the course, I explored both the potential and the limitations of AI. It’s a fascinating technology with huge possibilities—though its inner workings often reveal a lack of true intelligence. I realized how important it is to evaluate whether a model generates trustworthy outputs, and to monitor its use to prevent misuse—like malicious prompts or inappropriate content generation.
AI development brings both opportunities and challenges. On the one hand, it can support us in daily tasks such as automation and education (where it clearly shows great promise). On the other hand, it raises questions about ethics, the future of the job market, and the need for global regulations (though who exactly would enforce those?..).
Thank you to the course organizers at Elephant AI, and especially to instructor Konrad Banachewicz, for such an intense and well-rounded program. Despite my prior experience with AI, this course gave me a much more complete picture—from practical tools to the less obvious aspects I hadn’t considered before. The knowledge I gained has significantly expanded my skill set and opened up new perspectives in working with AI.
Damian Augustyn
Product Manager | +5 years in tech | AI practitioner | PMI-ACP | PSPO II
I’m happy to share that I’ve completed the GenAI Code certification from Elephant AI!
TL;DR – what you can take away from this course:
Working with all kinds of multimodal models, combining them, and implementing directly in code.
Prompt engineering
Model fine-tuning using LoRA (example in the photo: using a fine-tuned FLUX model on my own images)
RAG using various document types: pdf, img, csv, xls.
Evaluating and refining RAG-based implementations, verifying answer accuracy metrics.
Big congrats and thanks to Konrad Banachewicz – you set a demanding pace, but thanks to that, the level of “substance” in this course was truly high! Well done!
Thanks also to Maria Parysz and Alex Kwiatkowski for organizing Elephant AI – you’re doing an amazing job!
What’s next? Agents 🤖
Grzegorz Józefiak
IT Project manager, AI Manager
I’ve completed the 6-week GenAI Code course organized by Elephant AI! 🎉 And it was a perfect choice. Huge thanks to Konrad Banachewicz for the substance, the calm analytical approach, the sense of humor with just the right edge—and for an absolutely fascinating journey through the world of Generative AI.
The technology we now call AI carries immense power, offering both opportunities and risks that need to be felt and understood. Experiencing the differences between local and cloud processing environments, open-source models and those accessed via API, and going from mono- and multimodal models through RAG, evaluation, and solution monitoring—that’s the foundation I needed to have… and now I do.
For someone like me, whose journey with software, systems, and machines began back when computers existed only in large computing centers, this was another step in staying up to date with technology. Six weeks in theory, but in practice it was months of intense analysis and case studies to build my own environment—a space where I can continue experimenting so that the AI-driven components in the projects I manage deliver real business value.
Many thanks—and now I’m diving into “AI Agents Solutions for the Future”, continuing the journey with Elephant AI.
Kamil Winiarski
Senior Technical Support Specialist | AI Enthusiast | Exploring the Future of Machine Learning and Automation | Thinker. Innovator. AI Explorer | Cybersecurity
🤖 I'm excited to share that I’ve earned the Elephant AI – GenAI Code certificate from Elephant AI!
I’m grateful for the opportunity to grow and for reaching this milestone.
Over 6 intense weeks, I gained knowledge in the following areas:
🔹 Applying AI and large language models (𝗟𝗟𝗠s) to various modalities such as text, image, audio, and video
🔹 Coding useful solutions in 𝗣𝘆𝘁𝗵𝗼𝗻, including chatbots and image generators
🔹 Fine-tuning LLMs and using Retrieval-Augmented Generation (𝗥𝗔𝗚) to produce more accurate text outputs
🔹 Implementing, evaluating, and monitoring 𝗚𝗲𝗻𝗔𝗜 solutions based on LLMs, and deploying them in cloud environments
To complete the course, I had to pass all 10 module assessments and succeed in a Kaggle challenge. During the final task, I built a script capable of solving a specific problem—an experience that truly tested and validated what I’d learned.
Benjamin Kadzioch
Project Manager | Program Manager | AI Consultant | GenAI | AI Agents | Native German
I am excited to share that I have received a new certificate 𝗚𝗲𝗻𝗔𝗜 𝗖𝗼𝗱𝗲 from Elephant AI! These were 6 weeks of intensive coding experience confirmed by a final capstone coding project: 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗔𝗜 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗮𝗻𝘀𝘄𝗲𝗿𝗶𝗻𝗴 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 𝗮𝗯𝗼𝘂𝘁 𝗪𝗵𝗶𝘀𝘁𝗹𝗲𝗯𝗹𝗼𝘄𝗲𝗿 𝗟𝗮𝘄 𝘂𝘀𝗶𝗻𝗴 𝗟𝗟𝗠 𝗮𝗻𝗱 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲.
During the course I have learned how to work with:
🐍 𝗣𝘆𝘁𝗵𝗼𝗻 (using libraries like Transformers, PyTorch, OpenCV, Fitz/PyMuPDF, LangChain etc.)
🔤 𝗧𝗲𝘅𝘁:
Building Assistants and Chatbots via API or using Open-Source LLM’s executed locally or with use of GPU
LLM Fine-Tuning
🏙 𝗜𝗺𝗮𝗴𝗲:
Generation and Edition using Open-Source Models (e.g. Stable Diffusion)
Fine-Tuning with own images
Use of User Interfaces (UI) for Proof of Concept (PoC) purposes
🔈 𝗩𝗼𝗶𝗰𝗲/𝗔𝘂𝗱𝗶𝗼:
Voice transcription
Text-to-speech
Music/Audio generation
Building Voice Assistants
📽 𝗩𝗶𝗱𝗲𝗼:
Text-to-video
Image-to-video
Video-to-video
Transcription and summary of videos with translation and speech generation
🤖 𝗠𝘂𝗹𝘁𝗶𝗺𝗼𝗱𝗮𝗹 𝗠𝗼𝗱𝗲𝗹𝘀:
Describing images (based on VLM - Vision Language Models)
Converting text images into editable formats (OCR)
Extracting information from video in order to generate video description or voiceover script
Slide narration based on PowerPoint presentations
🗃 𝗥𝗔𝗚 𝗔𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲:
Uploading own documents and extracting information from PDF, Excel, Word etc. (e.g. LllamaIndex)
Use of Vector Databases (e.g. Chroma)
Use of Knowledge Graphs (e.g. GraphRAG)
Multimodal RAG
🎯 𝗟𝗟𝗠 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻 (e.g. DeepEval, Giskard, Ragas):
Answer Relevancy
Faithfulness
Contextual Precision
Contextual Recall
Hallucinations
Bias
Toxicity
📊 𝗟𝗟𝗠 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴 (e.g. Llama Guard, Prompt Guard, LangKit):
Safety
Prompt Injection
Jailbreaks
👏 Many thanks to Konrad Banachewicz for transferring knowledge in such a wonderful way!
🚀 Next stop: Building 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀!
Maciej Wnuk
Compliance, anti-corruption, whistleblowers, ethics – well-received trainings, effective implementations
📕 If you’re not expanding your knowledge, you’re falling behind!
📕 I’m proud to share that I’ve completed the intensive GenAI Code course, led by Konrad Banachewicz and organized by Elephant AI.
📕 Throughout the course, of course, we had to complete mandatory homework assignments—and finish with a final project.
📕 Mr. Konrad shared an incredible amount of theoretical knowledge and its practical applications—plenty of material to reflect on and continue exploring for months to come.
📕 Getting a peek behind the curtain of artificial intelligence and experimenting with its more advanced uses on my own was a fantastic adventure.
🍎 Especially considering how fast AI is entering our professional lives—faster than personal computers did back in the day.
Dominik Dobry
Scrum Master in STS GG and Agile leadership apprentice
I’m not a programmer, and I’m not planning to become one—but this certificate holds special meaning for me for several reasons:
➡ Self-recognition – In a world where expectations are constantly growing, 6 weeks of intense work, learning, and challenges is something worth celebrating.
➡ Reflection on the role of a Scrum Master and Agile Coach – These roles are often reduced to simple labels: “meeting organizer,” “consultant,” or “Scrum enforcer.” In reality, the people I know in these roles—myself included—are on the front lines of organizational change. As first adopters and first followers, we don’t just support transformations; we help inspire and shape new directions. This certificate is proof that continuous growth is possible, even in a fast-changing world.
➡ Gratitude to the Elephant AI community – Maria Parysz and Konrad Banachewicz are doing something incredible by creating a space for education and growth in the GenAI space. Thanks to them, the community feels like a peloton—encouraging, supportive, and helping everyone catch up with the rapid pace of technology. Without their open and inclusive approach, this certificate wouldn’t have been possible.
To me, this certificate doesn’t mean I’ll start coding—but it does give me the tools to:
better understand the potential of GenAI,
inspire more technical people to take action,
and support teams and organizations in building future-ready environments.
Konrad Juszczuk
Digital Transformation | Controlling Solutions | AI | Business Analyst | Financial Controller
Thrilled to share that I’ve just completed the ‘GenAI Code’ course, a deep dive into the world of AI, skillfully orchestrated by Konrad Banachewicz and offered by Elephant AI.
As always, Konrad Banachewicz managed to make the complex look easy—guess that’s just another day at the office for us coding enthusiasts! Excited to apply these new skills in my work. A huge thank you to the Elephant AI team and Konrad for the knowledge and the fun journey. Here’s to many more lines of code and fewer bugs in our future! 🚀
Bartosz Urban
Python | Data Analytics | GenAI | BI | AdTech
💡 A new chapter in my tech journey!
I’m thrilled to share that I’ve earned the Elephant AI – GenAI Code certificate from Elephant AI! It was 6 intense weeks of learning that helped me develop hands-on skills in the field of Generative AI.
During the course, I explored:
🔹 Coding GenAI-based solutions in Python, including chatbot and image generator development
🔹 Applying large language models (LLMs) across multiple modalities: text, images, audio, and video
🔹 Fine-tuning LLMs and using RAG (Retrieval-Augmented Generation) to generate more accurate results
🔹 Implementing, evaluating, and deploying GenAI solutions
I work with AI on a daily basis, and the knowledge I’ve gained will help me deliver even better results and develop innovative, AI-powered solutions. I can’t wait to put these skills into practice! 🚀
Join the course
Fall 2025
Edition
3.
GenAI
Code
6 weeks of learning in the GenAI Code program led by Konrad Banachewicz, PhD, Kaggle Grandmaster
20+ hours of LIVE workshops
International experts and guest instructors
6-month access to all recordings and materials
Hands-on homework assignments
Real-world solution deployment
Commercial product development
Starter materials included
DIY scripts and projects
Final challenge to complete the course
Recognized and trusted Elephant AI certificate with a detailed skills supplement
2990
PLN
or two installments x
1495 PLN
7-Day Guarantee
The course lasts 10 weeks. You have the right to cancel within 7 days of the course start date. This means you can go through the first week of the course, and if you decide it’s not for you or you don’t have time for it, we will refund 100% of your payment. You risk nothing — we operate in full trust.
0% Installments
You can split your payment into 2 installments at 0% interest. The first is paid upfront, the second within 7 days of the course start date. We handle installments ourselves, not through a bank, so it won’t affect your credit score. We operate fully in trust.
Training Budget Financing
Many of our participants choose to finance the course using their company’s training budget. Contact us at contact@elephantai.io if you need a proforma invoice for internal approval. For teams of 3 or more, we offer special discounts.
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Join the course
Fall 2025
Edition
3.
GenAI
Code
6 weeks of learning in the GenAI Code program led by Konrad Banachewicz, PhD, Kaggle Grandmaster
20+ hours of LIVE workshops
International experts and guest instructors
6-month access to all recordings and materials
Hands-on homework assignments
Real-world solution deployment
Commercial product development
Starter materials included
DIY scripts and projects
Final challenge to complete the course
Recognized and trusted Elephant AI certificate with a detailed skills supplement
2990
PLN
or two installments x
1495 PLN
7-Day Guarantee
The course lasts 10 weeks. You have the right to cancel within 7 days of the course start date. This means you can go through the first week of the course, and if you decide it’s not for you or you don’t have time for it, we will refund 100% of your payment. You risk nothing — we operate in full trust.
0% Installments
You can split your payment into 2 installments at 0% interest. The first is paid upfront, the second within 7 days of the course start date. We handle installments ourselves, not through a bank, so it won’t affect your credit score. We operate fully in trust.
Training Budget Financing
Many of our participants choose to finance the course using their company’s training budget. Contact us at contact@elephantai.io if you need a proforma invoice for internal approval. For teams of 3 or more, we offer special discounts.
Need more time?
Join the waitlist!
By filling out the form, you accept the Privacy Policy and agree to join the Elephant AI newsletter managed by Maria Parysz and ElephantAI Ltd. We ensure no spam. You can unsubscribe at any time.
+
members of Elephant AI community
+
students on LinkedIn Learning
Join the course
Fall 2025
Edition
3.
GenAI
Code
6 weeks of learning in the GenAI Code program led by Konrad Banachewicz, PhD, Kaggle Grandmaster
20+ hours of LIVE workshops
International experts and guest instructors
6-month access to all recordings and materials
Hands-on homework assignments
Real-world solution deployment
Commercial product development
Starter materials included
DIY scripts and projects
Final challenge to complete the course
Recognized and trusted Elephant AI certificate with a detailed skills supplement
2990
PLN
or two installments x
1495 PLN
7-Day Guarantee
The course lasts 10 weeks. You have the right to cancel within 7 days of the course start date. This means you can go through the first week of the course, and if you decide it’s not for you or you don’t have time for it, we will refund 100% of your payment. You risk nothing — we operate in full trust.
0% Installments
You can split your payment into 2 installments at 0% interest. The first is paid upfront, the second within 7 days of the course start date. We handle installments ourselves, not through a bank, so it won’t affect your credit score. We operate fully in trust.
Training Budget Financing
Many of our participants choose to finance the course using their company’s training budget. Contact us at contact@elephantai.io if you need a proforma invoice for internal approval. For teams of 3 or more, we offer special discounts.
Need more time?
Join the waitlist!
By filling out the form, you accept the Privacy Policy and agree to join the Elephant AI newsletter managed by Maria Parysz and ElephantAI Ltd. We ensure no spam. You can unsubscribe at any time.
+
members of Elephant AI community
+
students on LinkedIn Learning
Join the course
Fall 2025
Edition
3.
GenAI
Code
6 weeks of learning in the GenAI Code program led by Konrad Banachewicz, PhD, Kaggle Grandmaster
20+ hours of LIVE workshops
International experts and guest instructors
6-month access to all recordings and materials
Hands-on homework assignments
Real-world solution deployment
Commercial product development
Starter materials included
DIY scripts and projects
Final challenge to complete the course
Recognized and trusted Elephant AI certificate with a detailed skills supplement
2990
PLN
or two installments x
1495 PLN
7-Day Guarantee
The course lasts 10 weeks. You have the right to cancel within 7 days of the course start date. This means you can go through the first week of the course, and if you decide it’s not for you or you don’t have time for it, we will refund 100% of your payment. You risk nothing — we operate in full trust.
0% Installments
You can split your payment into 2 installments at 0% interest. The first is paid upfront, the second within 7 days of the course start date. We handle installments ourselves, not through a bank, so it won’t affect your credit score. We operate fully in trust.
Training Budget Financing
Many of our participants choose to finance the course using their company’s training budget. Contact us at contact@elephantai.io if you need a proforma invoice for internal approval. For teams of 3 or more, we offer special discounts.
Need more time?
Join the waitlist!
By filling out the form, you accept the Privacy Policy and agree to join the Elephant AI newsletter managed by Maria Parysz and ElephantAI Ltd. We ensure no spam. You can unsubscribe at any time.
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AI Transformation
Comprehensive assistance with AI transformation in your business. We provide support at every stage.
Strategic meetings
Individual inspirational sessions with our experts, building awareness in artificial intelligence.
Workshops
Corporate training sessions at convenient times and on selected topics, complemented by industry sessions that periodically refresh knowledge.
Online courses
Cohort courses – convenient home learning for managers and specialists. Check the latest editions and course calendar!
Are you looking for something else?
Fill out the form
Contact us so we can find the best solution for your needs
How can we help you?
AI Transformation
Comprehensive assistance with AI transformation in your business. We provide support at every stage.
Strategic meetings
Individual inspirational sessions with our experts, building awareness in artificial intelligence.
Workshops
Corporate training sessions at convenient times and on selected topics, complemented by industry sessions that periodically refresh knowledge.
Online courses
Cohort courses – convenient home learning for managers and specialists. Check the latest editions and course calendar!
Are you looking for something else?
Fill out the form
Contact us so we can find the best solution for your needs
How can we help you?
AI Transformation
Comprehensive assistance with AI transformation in your business. We provide support at every stage.
Strategic meetings
Individual inspirational sessions with our experts, building awareness in artificial intelligence.
Workshops
Corporate training sessions at convenient times and on selected topics, complemented by industry sessions that periodically refresh knowledge.
Online courses
Cohort courses – convenient home learning for managers and specialists. Check the latest editions and course calendar!
Are you looking for something else?
Fill out the form
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Do you want to integrate AI into your life? We have a gift for you
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By filling out the form, you accept the Privacy Policy and agree to join the Elephant AI newsletter managed by Maria Parysz and ElephantAI Ltd. We ensure no spam. You can unsubscribe at any time.
Do you want to integrate AI into your life? We have a gift for you
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By filling out the form, you accept the Privacy Policy and agree to join the Elephant AI newsletter managed by Maria Parysz and ElephantAI Ltd. We ensure no spam. You can unsubscribe at any time.
Do you want to integrate AI into your life? We have a gift for you
We prepared three free lessons from the "AI for Managers" course and a list of 70 AI tools we recommend.
By filling out the form, you accept the Privacy Policy and agree to join the Elephant AI newsletter managed by Maria Parysz and ElephantAI Ltd. We ensure no spam. You can unsubscribe at any time.
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© 2023 Elephant AI Inc., Canada. All rights reserved.
© 2023 Elephant AI Inc., Canada. All rights reserved.
© 2023 Elephant AI Inc., Canada. All rights reserved.