Online
Students learn the ML basics at their own pace
Machine Learning Essentials for Coders
Designed for professionals seeking skills to launch their own LLM-powered projects
LLM Engineering Essentials
Participants develop practical GenAI expertise and elevate their ML careers
Practical Generative AI
Ideal for those based in London and eager to explore applications of LLMs
Intro to ML from an LLM standpoint
Leave your contact details, and we'll notify you about the next enrollment
Y-DATA
In-person
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At Nebius Academy, we empower engineers and researchers through expert-led courses and university partnerships.
Master AI.
Transform the future.
Collaborations with top institutions create an impact in both research and education.
University partnerships
We organize practice-oriented online and in-person courses in Tel Aviv and London for data and ML professionals.
Advanced training
Our cloud grants give students and academic partners access to extra computational resources.
Research support
About the Academy
Our university partnerships and advanced online and in-person programs in data science, machine learning, and generative AI help specialists level up their skills and drive innovation in tech.
Join us in shaping the future
Environment where data professionals can grow.
How we support research
These grants can be used for building multimodal generative models, developing novel deep learning architectures, and more.
Limited computational resources mean limited research. To support AI progress, we offer cloud grants to students and partners from academia.
Our courses are created and taught by experts from all walks of life. They bring a mix of deep theoretical knowledge and practical expertise to our students.
Our team
Elena Bunina
Anna Veronica Dorogush
Eugenia Kulikova
Inbar Huberman
Head of Nebius Academy
Founder and CEO of Recraft
Head of university relations
Academic lead at Y-Data
Elena is a professor at Bar Ilan University. She enjoys teaching students and doing research in Algebra and Model Theory. She also leads the Teachers for Israel initiative.
Anna Veronika Dorogush is the founder and CEO of Recraft, a company specializing in generative AI for creating professional designs.
Evgenia is a highly experienced professional in the field of educational services.
Inbar is a postdoc researcher at Technion. She has got her PhD at the Hebrew University of Jerusalem. Her research is focused on image processing and generation, in particular with diffusion models.
Niv Haim
Stanislav Fedotov
Victor Lempitsky
Sergei Petrov
Lecturer at Generative AI course
AI content lead at Nebius Academy
Advisory Board Member
Lecturer at Generative AI course
Niv Haim is a computer vision and machine learning researcher at the Weizmann Institute of Science, where he earned his PhD under the guidance of Prof. Michal Irani.
Stanislav started his career as a mathematician, but later he switched to creation and management of educational projects in Data Science.
Victor Lempitsky is currently Chief Science Officer and Founder of the Cinemersive Labs Ltd company.
He obtained an Engineering MSc degree at Stanford University, his research was focused on Computer Vision applications for Earth Science.
In-person courses
Get a chance to discuss concepts, network, and share experiences with fellow data and AI professionals
Educational programs
Taught at the Tel Aviv University campus
Y-DATA
An intensive, one-year career advancement course in data science that bridges the gap between short-term online studies and full-time MSc programs.
Applications are closed
Intro to ML from an LLM standpoint
Developed and presented by experts from academia and industry, our 3.5-month program is ideal for data scientists, software engineers, and developers motivated to study the basics of machine learning and applications of large language models.
Taught in London
Leave your contact details, and we'll notify you about the next enrollment
Online courses
Programs crafted specifically for busy professionals with full-time work schedules
Applications are open
Practical Generative AI
Over 4–6 months, explore GenAI best practices, learn how large language models work, and master integrating generative AI into various applications to take your career to the next level — all with guidance from industry professionals.
Applications are open
ML Essentials for Coders
This short, self-paced course is packed with useful materials, perfect for those with no prior machine learning knowledge looking to learn ML basics and their application in real-world scenarios.
Applications are open
LLM Engineering Essentials
This advanced program helps ML engineers, data scientists, and software developers explore what LLMs are and how to deploy an open-source model in the cloud — all with support from GenAI engineers and researchers.
Future-Proof Your Team’s Tech Skills
Empower your team with tailored training in AI, data, and ML, plus smart AI-driven assessments, ensuring the right talent in the right roles.
Hear from our students
Arseny Levin
Fraud Detection Lead at DoubleVerify
Great experience so far! Personally for me, the course exceeded my expectations. I usually stay away from courses since I'm a self learner. Courses usually spend too much time on the unimportant parts (too much history, too much theory, repetitive exercises etc.).
However during Y-DATA courses we ha exactly the right balance of practice and theory.
Y-DATA
Andrey Nikitin
Data scientist at Wix
The course is great, I think it's the best professional course I have taken and for me personally it's a good substitution to a master degree (for now). Even though I'm already working as a Data Scientist i still learn new things, there are always fields that I'm less proficient in and the course fills the gap.
Y-DATA
Tal Ben-Yehuda Heletz
Deep Learning Researches at Trigo
It was obvious to me that math is the field for me. I did my B.Sc and M.Sc in math. In the industry, you can do a lot with math, but you must have knowledge in computer science as well.
Y-DATA
Y-Data was exactly right for me - it let me combine my background with computer science and strong data science foundations.
Liad Yosef
Client Architect at Duda
You know they say go with your passion, right? I've been programming since I was a kid, but I never really dealt with Data Science or Machine Learning before Y-Data. I already knew the math part of the introductory courses but they were so fast-paced that I wasn't bored and quickly enough we got into supervised learning and deep learning. This gave me the tools to do things that I coundn't have done before, let me explore and widen the area of my thoughts.
Y-DATA
Jonathan Ohnona
Data Scientist at eToro
I'm an Engineer. I studied math and physics, and financial engineering. I choose Y-DATA because I wanted a better understanding of the algoritms. When you have access to machine learning techniques, you have access to more tools, allowing you to do more things. For instance, in my field, in time-series analysis, you want to better predict and better focus. Studying in Y-DATA is like building a muscle. You need to work on a muscle to be a better, stronger person. It's a very good program because it shows many things.
Y-DATA
Alexander Kazakov
OCR
Hello, my name is Alexander Kazakov, and I work with OCR and text extraction from images and PDF files at Megaputer Intelligence, a company specializing in text data analysis.
My decision to study in the Generative AI program stemmed from a desire to learn something new...
Generative AI
Computer Vision
Machine Learning
ML
Andi Mardinsyah
Data Scientist
Hello! My name is Andi Mardinsyah, and I work as a Data Scientist at Telekomunikasi Indonesia.
My company is currently working on creating applications for natural language processing...
Generative AI
Emanuele Bezzecchi
AI Roadmap Manager
The videos taught me a lot and give a better understanding of LLMs, really helpful in my job I underestimate the ratio between free time/time needed to do the homework.
I like to really understand what I’m doing and so I do not finish 3 of the 5 homework...
Generative AI
Ahmad Zeidan
Developer Support Engineer
The course over all is great I'm enjoying it so far, the videos are vary good and easy to understand, long format reading and papers are ok as well, I'm kinda used to reading similar things in university, and have gpt-4 to help 🙂
Generative AI
Emanuele Antonioni
Machine Learning Engineer
Until now I am finding the course great! I really enjoyed the first two classes, the third was a bit less practical but still really interesting. The homeworks are really good, maybe sometimes a bit too long, but really enjoyable. Until now my feedback is totally positive.
Generative AI
Igor Samenko
DS, ML & DL Engineer
The course is great! I really like it!I like the amount of new material and the number of articles (referenced in the lectures). I believe that the knowledge gained in this course will be highly relevant for the next few years. Personally, I like the more technical...
Generative AI
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Ahmad Zeidan
Developer Support Engineer
The course over all is great I'm enjoying it so far, the videos are vary good and easy to understand, long format reading and papers are ok as well, I'm kinda used to reading similar things in university, and have gpt-4 to help 🙂
Generative AI
Arseny Levin
Fraud Detection Lead at DoubleVerify
Great experience so far! Personally for me, the course exceeded my expectations. I usually stay away from courses since I'm a self learner. Courses usually spend too much time on the unimportant parts (too much history, too much theory, repetitive exercises etc.).
However during Y-DATA courses we ha exactly the right balance of practice and theory.
However during Y-DATA courses we ha exactly the right balance of practice and theory.
Y-DATA
Alexander Kazakov
Hello, my name is Alexander Kazakov, and I work with OCR and text extraction from images and PDF files at Megaputer Intelligence, a company specializing in text data analysis.
My decision to study in the Generative AI program stemmed from a desire to learn something new. This choice was driven by my aim to keep up with modern technologies and the latest developments. In my work, I already have experience in training neural networks, but in a different area and on a smaller scale.
The module proved to be very informative, and the provided educational materials were relevant to me. I'd like to note the availability of experts for discussions; they respond quickly and comprehensively to questions. On average, I spent 15 to 20 hours per week on the training, but I believe the pace of learning is individual.
Particularly memorable was the first week of the program, an introduction to LLMs led by lecturer Yuval Belfer. The new information and understanding of previously complex concepts as simpler opened new horizons for thinking and action.
The practical assignments were also interesting, especially the last project on information extraction from databases.
The only aspect I'd like to see improved is a deeper exploration of theory. I've already provided this feedback to the team, and they explained that this is a characteristic of the first module. The second module promises a more extensive study of theory. We'll see.
I like the program and trust its creators. I would recommend it to my colleagues involved in machine learning and text analysis. I think the first module might seem less interesting to them due to their existing knowledge, but the second module will be beneficial for a deeper dive into theory and the mechanics of model operation. For those familiar with programming but new to neural networks, the first module will be particularly interesting.
My decision to study in the Generative AI program stemmed from a desire to learn something new. This choice was driven by my aim to keep up with modern technologies and the latest developments. In my work, I already have experience in training neural networks, but in a different area and on a smaller scale.
The module proved to be very informative, and the provided educational materials were relevant to me. I'd like to note the availability of experts for discussions; they respond quickly and comprehensively to questions. On average, I spent 15 to 20 hours per week on the training, but I believe the pace of learning is individual.
Particularly memorable was the first week of the program, an introduction to LLMs led by lecturer Yuval Belfer. The new information and understanding of previously complex concepts as simpler opened new horizons for thinking and action.
The practical assignments were also interesting, especially the last project on information extraction from databases.
The only aspect I'd like to see improved is a deeper exploration of theory. I've already provided this feedback to the team, and they explained that this is a characteristic of the first module. The second module promises a more extensive study of theory. We'll see.
I like the program and trust its creators. I would recommend it to my colleagues involved in machine learning and text analysis. I think the first module might seem less interesting to them due to their existing knowledge, but the second module will be beneficial for a deeper dive into theory and the mechanics of model operation. For those familiar with programming but new to neural networks, the first module will be particularly interesting.
Generative AI
OCR
Computer Vision
Machine Learning
ML
Andrey Nikitin
Data scientist at Wix
The course is great, I think it's the best professional course I have taken and for me personally it's a good substitution to a master degree (for now). Even though I'm already working as a Data Scientist i still learn new things, there are always fields that I'm less proficient in and the course fills the gap.
Y-DATA
Emanuele Bezzecchi
The videos taught me a lot and give a better understanding of LLMs, really helpful in my job I underestimate the ratio between free time/time needed to do the homework.
I like to really understand what I’m doing and so I do not finish 3 of the 5 homework. As example here is 7:38 in the morning and 7-8 in the morning is the only slot available in these weeks for me to follow lessons/do homework.
Anyway now that I get the way you teach I can honestly say that the technical content is good and I think to have spent my money in a good way. That’s my feeling.
I like to really understand what I’m doing and so I do not finish 3 of the 5 homework. As example here is 7:38 in the morning and 7-8 in the morning is the only slot available in these weeks for me to follow lessons/do homework.
Anyway now that I get the way you teach I can honestly say that the technical content is good and I think to have spent my money in a good way. That’s my feeling.
Generative AI
AI Roadmap Manager
Tal Ben-Yehuda Heletz
Deep Learning Researches at Trigo
It was obvious to me that math is the field for me. I did my B.Sc and M.Sc in math. In the industry, you can do a lot with math, but you must have knowledge in computer science as well.
Y-Data was exactly right for me - it let me combine my background with computer science and strong data science foundations.
Y-Data was exactly right for me - it let me combine my background with computer science and strong data science foundations.
Y-DATA
Andi Mardinsyah
Hello! My name is Andi Mardinsyah, and I work as a Data Scientist at Telekomunikasi Indonesia.
My company is currently working on creating applications for natural language processing, such as segment analysis, and also on projects related to LLM. That's why I decided to study in the Generative AI program – to understand this topic deeper and solve work tasks more effectively.
I had to choose between two Generative AI programs, but I chose the program from Nebius Academy because I really liked its curriculum. As you know, generative AI is everywhere now, and the technologies are developing very fast. It's hard to find an educational program that combines both theory and practice. In my opinion, the curriculum of this program is very complete and comprehensive.
I have finished the first module of the program, which is dedicated to Generative AI applications. I really liked this module and found it extremely useful. Although I am a data analysis specialist and new to Generative AI, I can confidently say that my time was well spent. Especially valuable was the fact that we did a lot of coding during the training, which is an important part of the educational process.
Besides the program content, I would like to highlight its organization. I have a busy work schedule and doubted if I could combine work and study. I assumed the lectures would be long, but was pleasantly surprised to find out that the recorded lectures last only 15 minutes and cover a lot of material. This allows me to spend more time on practical tasks, which are plentiful in the program. It's important to note here that this is not just one 15-minute lecture per week, there are usually several.
I will definitely recommend this program to my colleagues.
I think these materials will be useful for all Data Scientists who are involved in natural language processing and LLM.
My company is currently working on creating applications for natural language processing, such as segment analysis, and also on projects related to LLM. That's why I decided to study in the Generative AI program – to understand this topic deeper and solve work tasks more effectively.
I had to choose between two Generative AI programs, but I chose the program from Nebius Academy because I really liked its curriculum. As you know, generative AI is everywhere now, and the technologies are developing very fast. It's hard to find an educational program that combines both theory and practice. In my opinion, the curriculum of this program is very complete and comprehensive.
I have finished the first module of the program, which is dedicated to Generative AI applications. I really liked this module and found it extremely useful. Although I am a data analysis specialist and new to Generative AI, I can confidently say that my time was well spent. Especially valuable was the fact that we did a lot of coding during the training, which is an important part of the educational process.
Besides the program content, I would like to highlight its organization. I have a busy work schedule and doubted if I could combine work and study. I assumed the lectures would be long, but was pleasantly surprised to find out that the recorded lectures last only 15 minutes and cover a lot of material. This allows me to spend more time on practical tasks, which are plentiful in the program. It's important to note here that this is not just one 15-minute lecture per week, there are usually several.
I will definitely recommend this program to my colleagues.
I think these materials will be useful for all Data Scientists who are involved in natural language processing and LLM.
Generative AI
Data Scientist
Liad Yosef
Client Architect at Duda
You know they say go with your passion, right? I've been programming since I was a kid, but I never really dealt with Data Science or Machine Learning before Y-Data. I already knew the math part of the introductory courses but they were so fast-paced that I wasn't bored and quickly enough we got into supervised learning and deep learning. This gave me the tools to do things that I coundn't have done before, let me explore and widen the area of my thoughts.
Y-DATA
Emanuele Antonioni
Until now I am finding the course great! I really enjoyed the first two classes, the third was a bit less practical but still really interesting. The homeworks are really good, maybe sometimes a bit too long, but really enjoyable. Until now my feedback is totally positive.
Generative AI
Machine Learning Engineer
Jonathan Ohnona
Data Scientist at eToro
I'm an Engineer. I studied math and physics, and financial engineering. I choose Y-DATA because I wanted a better understanding of the algoritms. When you have access to machine learning techniques, you have access to more tools, allowing you to do more things. For instance, in my field, in time-series analysis, you want to better predict and better focus. Studying in Y-DATA is like building a muscle. You need to work on a muscle to be a better, stronger person. It's a very good program because it shows many things.
Y-DATA
Igor Samenko
The course is great! I really like it!I like the amount of new material and the number of articles (referenced in the lectures). I believe that the knowledge gained in this course will be highly relevant for the next few years. Personally, I like the more technical (theoretical) dive into technology and into math but I realize the course has a different format and that's fine with me.
The teaching team is wonderful. Quality of lectures and presented material 10/10. I like the lecturers and how they present the material. I see passionate people who love what they do.
I like the course syllabus and that the course gives a wide overview of many areas. But, the topics "Bias in Generative AI" and "AI safety" are currently the most controversial for me. I mean, yeah, it's "good to know" information. But it's not deep enough for me to be useful or something I could apply to my work/life.
The material in the long reads is well prepared, compressed and interesting. I like that the lectures don't give 100% on the answers in quize and you have to work to get the knowledge for the right answer.
I also like that the homework is based on new, actual technology. Also the "paperwatch" channel is a treasure trove of recent hot topics. Really love it ❤️ I hope to be able to keep access to this channel after the course finishes.
The teaching team is wonderful. Quality of lectures and presented material 10/10. I like the lecturers and how they present the material. I see passionate people who love what they do.
I like the course syllabus and that the course gives a wide overview of many areas. But, the topics "Bias in Generative AI" and "AI safety" are currently the most controversial for me. I mean, yeah, it's "good to know" information. But it's not deep enough for me to be useful or something I could apply to my work/life.
The material in the long reads is well prepared, compressed and interesting. I like that the lectures don't give 100% on the answers in quize and you have to work to get the knowledge for the right answer.
I also like that the homework is based on new, actual technology. Also the "paperwatch" channel is a treasure trove of recent hot topics. Really love it ❤️ I hope to be able to keep access to this channel after the course finishes.
Generative AI
DS, ML & DL Engineer