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At Nebius Academy, we drive AI forward with expert-led educational courses and collaborations with academia.
By powering up learning, research, and innovation, we help AI shape the future.
To drive change and make an impact in research and education, we collaborate with top institutions.
University partnerships
We organize practice-oriented online and in-person courses in Tel Aviv and London, designed by experts from academia and industry for data and AI professionals.
Advanced training
The need for computational resources can limit research. To support the AI progress, we offer cloud grants to our students and partners from academia.
Research projects
About School
Our advanced online and offline educational programs in data science and generative AI combine pioneering research and solid industry expertise. They are designed for specialists eager to level up their skills and drive innovation in tech.
Learning with us
Environment where data professionals can grow.
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.
Our Projects
Y-DATA
Y-DATA is an intensive one-year career advancement program in data science that bridges the gap between short-term online courses and a full-time MSc-level program.
Y-DATA is designed by top-notch experts from the academy and the industry and taught at Tel Aviv University campus. The program is localized to enhance the Israeli tech community and the global AI ecosystem.
Applications are open
Learn, Practice, Launch
Our 250‑hour curriculum was designed after analysis of the current state of data science education in Israel. Y‑DATA aims to provide the skills required for entry and mid‑level data science jobs in the local ecosystem.
In-person at Tel-Aviv
An intensive curriculum of over 250 hours designed to equip students with the necessary skills for entry to mid-level data science positions within the Israeli tech industry.
1 year
You will engage in focused, short-duration courses dives into specific topics, including Supervised and Unsupervised Learning, Deep Learning and advanced ML applications.
Alumni Community
Y-DATA is more than just a single training program. It is an environment in which data professionals can grow.
Top-notch experts from the academy and the industry
Generative AI
Beginning with a practical exploration of Generative AI applications and best practices in its safe and responsible use, the course then dives deeper into the inner workings of generative models including Large Language Models (LLMs).
Throughout this journey, our seasoned industry experts provide real-world demonstrations on crafting Generative AI products and effectively integrating them into various applications.
Applications are open
Curriculum Designed for Professionals
To achieve full understanding of the use and application of Generative AI algorithms, our participants will work on a real-life project, translating theoretical knowledge into practical processes and overcoming realistic challenges.
Online
Our program is designed for busy professionals with full-time work commitments and the workload is designed to be manageable with a full-time job.
4-6 month
The course consists of two training modules and contains fundamental theory and practical parts.
Real-life Projects
Our participants will work on a real-life project, translating theoretical knowledge into practical processes and overcoming realistic challenges.
Top-notch experts from the academy and the industry
Machine Learning Essentials for Coders
Our course will guide you through machine learning basics and show you how it can be applied in real-world scenarios. No prior machine learning knowledge is required, but you’ll need a solid grasp of Python programming.
By the end of the course, you’ll have practical skills and a solid foundation in machine learning, ready to create your own projects.
Applications are open
Learning process
In this course, we’ll guide you through five clear and straightforward notebooks that introduce you to cutting-edge concepts.
Step-by-Step Learning
We’ll begin with simple examples and provide clear, step-by-step explanations on training machine learning models. Perfect for beginners!
Transformers & LLMs
Discover transformers & LLMs that power recent AI breakthroughs. Gain the knowledge to apply them in practice.
Foundation
By the end of the course, you'll have practical skills and a solid foundation in machine learning, ready to create your own projects.
Each notebook has two versions:
- A basic version has several simple coding tasks that will help you to get a grasp on the material,
- A version with solutions has all the tasks solved, so you can consult them if you get stuck or if you want to check yourself.
LLM Engineering Essentials
This advanced program is designed to help professionals explore what large language models are, understand how to deploy an open-source model in the cloud, and master both the fundamentals and latest industry trends — all with guidance from GenAI engineers and researchers.
After finishing the course, you will have the practical skills needed to launch your own LLM-powered project.
Applications are open
Open up new career opportunities
We’ve crafted this program specifically for ML engineers, data scientists, and software developers who are ready to take their expertise to the next level. You'll also have access to a group chat where you can ask questions and connect with other students.
Online
Learn anywhere, anytime. Our program is perfect for data and software specialists with full-time jobs and busy lives.
3-5 weeks
Take your time, study at your own pace — there’s no pressure. Discover new concepts across 3 theme blocks, practice, and have your assignments graded automatically. We recommend dedicating around 10 hours per week to your studies.
Free
There’s no tuition fee — enjoy the course and upgrade your skills for free.
Experts from academia and industry
Intro to ML from an LLM standpoint
Developed and presented by experienced industry professionals, our offline London course is perfect for those motivated to learn the basics of machine learning and applications of large language models.
With this program, we aim to enrich the professional community and help move the industry forward.
Applications are open
Deepen your expertise
After mastering ML and LLMs with us, data scientists, software engineers, and developers will be ready to explore new roles and career avenues in the field.
In-person in London
Expect up-to-date content, group discussions, and lots of practice. You’ll meet our experts and fellow students at a convenient coworking space we’ve carefully chosen (125 Kingsway, London WC2B 6NH).
3.5 months
This program is advanced and thorough, but we won’t rush things. You’ll spend 3 hours a week on studies while we cover 12 different topics.
Free
Enjoy the course and upgrade your skills with no tuition fee. Other courses from Nebius Academy also await if you finish wanting more.
Experts from academia and industry
Consider the Testimonials
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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Visit Nebius
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