Learn Practice Launch

LEARNING TRACKS

Choose Your Track

Select one of the three flexible tracks to match your background, goals, and schedule.
AI-Powered Data Science
Duration: 4 months
Workload: 160h lectures + 280h homework
Course starts: Oct 28
Hybrid at Tel Aviv University campus: live classroom + Zoom stream
Focus: statistical thinking and Data exploration, feature engineering, classical ML models and pipelines, GenAI applications and tools
Ideal for: Analysts, STEM graduates, software developers looking to build a strong foundation in data science
Price: 12,500₪
Applications now open
Applied Deep Learning & Generative AI
Duration: 4 months
Workload: 160h lectures + 280h homework
Course starts: March 17
Focus: Deep learning theory, real-world use cases in vision and NLP, LLMs foundations and usage, RAG, prompt engineering, and AI agents deployment
Ideal for: Experienced data professionals ready to deepen their expertise
Price: 12,500₪
Applications open January 2026
AI-Powered DS + Applied DL & GenAI
Hybrid at Tel Aviv University campus: live classroom + Zoom stream
Focus: A comprehensive data science journey — from data wrangling and classical ML to advanced deep learning and GenAI deployment
Option to add a real-world project with leading data companies
Ideal for: Career switchers aiming to enter the AI and data science field
Price: 23,000₪
Applications now open
ABOUT

What is Y-DATA

Y‑DATA is an applied education program in machine learning and AI
It bridges the gap between short-term online courses and full-time MSc studies. Founded by Nebius and supported by experts from leading tech companies and universities.

Taught at Tel Aviv University in hybrid mode, it offers hands-on training, real-world projects, and practical experience with both Nebius and industry-standard tools, preparing professionals for the global AI and tech landscape.

This year, you can choose from two tracks: AI-Powered Data Science or Applied Deep Learning & Generative AI — or combine both for a full DS skillset, including hands-on industry experience.
Target audience

Who is this for?

Code professionals from IT industry
Researchers and advanced degree graduates
Professionals from tech IDF units
Fresh university graduates looking for DS roles
Advantages

What will we provide

Go to Program
250
hours
250 hours
of intensive
in-person training
7
years
7 years
Over 7 years’ proven
experience in Israel
300+ graduates
300+ graduates
employed in top tech
companies
92% employement
92% employement
rate in DS/ML
positions
Dedicated
career center
Dedicated career center
and soft-skills workshops
tailored to industry needs
Real
projects
Real projects
Real-world industry
project for your portfolio
Cloud resources
Cloud resources
Access to cloud
computation resources with Nebius cloud
Networking and more
Networking and more
ongoing involvement with
a community of experts
Advantages

Y-DATA Advantages

Y-DATA offers a unique combination of advantages not found in other programs.
Advantage
Theoretical foundations
Real-world practice
Latest AI research
Careful candidate selection
Job-friendly format
Industry mentors
Compute access
Up-to-date course
Y-DATA
Online courses
Bootcamps
Advanced degrees
This comparison is generalized by nature and some private offline programs or advanced degrees in academy provide more than mentioned here. However, this table provides a fair look into the different paths available towards a data science career.
offer

What do we offer?

Go to Program
01
Strong theoretical foundations
  • Understanding from the ground up of core ML principles.
  • Specialized courses (6-14 weeks), covering topics across all the ranges from ML foundations to advanced, state‑of‑the-art applications.
02
Practical experience through real-world projects
  • Full cycle data science project in the industry.
  • Experience working with real data in real industry environments.
  • Proven industry experience.
03
Extensive hands-on practice
  • Learning through hands-on application of common tools and concepts.
  • Weekly coding assignments for in-depth understanding.
04
Community and networking
  • Access to an active community of Y-DATA graduates and mentors in the industry.
  • Career and innovation opportunities - meeting industry insiders.
05
Fluency in Python and all common DS tools and methods
  • Python basics: Scikit-learn, pandas, matplotlib, numpy and more.
  • Extensive experience in neural networks and their applications in NLP and computer vision, up to and including generative models.
06
Selective admission process to create a winning team
  • Heterogenous student community leading to mutual enrichment and opportunities.
  • Strict entry pre-requisites for a solid starting position and quick progress.
OUR PROJECTS
Industry projects
Full project catalog
For bundle students only
Global Text Edits & Feedback
in Wordtune AI Writing Assistant
Population based
book model
Automated Slide Retrieval, Adaptation
and Presentation Generation
Anomalous SAR Image
Detection
PHI Detection in Medical
Imaging (DICOM)
AI-Powered Knowledge
Enhancement for Hospitals
Developing Fairness and Reliability Metrics in LLM Embedding Space
Cellular insights into Tertiary Lymphoid Structures via single-cell and spatial omics
Time to Cancel
Prediction
Text-to-SQL Conversion for WAF Data Analysis
Entity & Sentiment Extraction
for Support Conversations
Medical procedure
extraction from documents
Enhancing ETA and energy consumption prediction through driving pattern analysis
A comparative analysis for xai methods package
Automatic product comprehension with llms
Document validation and extraction
Text clustering for care management quality performance
Grinvision foundation model
Genomic profile representation for prediction of drug response
Generative creation of newsletter campaigns
Client application classification using exposed information
Behavioral cross-session user identification
SQL injection detection in real time
Healthscope: medical classification and contextual analysis
Content recommendation engine for emails
Learn more
admission scheme
Y-DATA employs a rigorous selection process to ensure
a motivating and encouraging learning environment.

To achieve our results, we need to ensure our candidates have the availability and capability of succeeding in the intense study program we offer.
01
Application
The application steps are the same for all tracks — just choose the one that best fits your learning goals.

Submit your application by filling the form. You will receive an email providing further information about the test and the following stages of the process.
Apply now
02
Online Test
Take an online test assessing your analytical and programming skills.
03
Interview
Meet Y-DATA team in person or online and tell us more about your background, experience, and interests, as well as your motivation and goals for the program. A few technical questions might be asked during the interview.
feedback

Our Alumni

Andrey Nikitin
Data Science Manager, Cyera
The course is great, I think it's the best professional course I have taken and for me personally, it's a good substitution for a master's 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.
Liad Yosef
Principal Software Engineer, Shopify
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 couldn't have done before, and let me explore and widen the area of my thoughts.
Lior Tabori
Senior Data Scientist, Stampli
I wanted to get into the world of data and data science. I had a feeling that this field is mine. That was my main purpose, to get the most out of this program and out of the industry project. I think our learning group was most important in my experience. It was small but diverse. Everyone is a specialist in something a little bit different so we really helped each other. There are very good students in this program.
Rachel Shalom
Principal Data Scientist, Dell Technologies
I realized that as a product manager in a travel tech startup, I needed heavy tools to analyze data, do predictions and more. So I started checking all kinds of data science boot camps, and machine learning academies, but unlike most of them, Y-DATA looked realistic. I chose Y-DATA because one year is better in terms of understanding things. Also, I could combine it with my previous work.
Yechiel Levy
CTO at OptimalQ
In a young startup like the one I own, we are doing a bit of everything, from big data to DevOps to data science. As we grow bigger. algorithms get more complicated. I joined Y-DATA to understand my data team better. Now I can understand their work better, know how they're approaching the problem. It helps us move along much faster and bridges the gap between management, engineering and data science teams.
Ido Nissim
Data Engineer at AllCloud
I think the very best thing about the course is the people. The selection of the students for the course was really good. Heterogeneous people from all kinds of fields and different backgrounds - that's really good. We had some projects together, and worked as groups, which was a good way to get to know other people. We were all sitting in the classroom together, talking and trying to figure out how to do the homework later on. It's great.
Amit Alon
Data Scientist at KHealth
I was looking for the best place to get ML Background, to learn more techniques, better and wider knowledge, especially in deep learning, which I didn’t know everything about. I chose Y-Data because it was presented as a program that can mediate the gap between academia and industry. This was exactly what I was looking for. I don’t have professional experience in ML but Y-Data gave me a really good background so I can bring a lot to the table in addition to my research background.
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 had exactly the right balance of practice and theory.
Nir Aviv
Software Engineer and Data Scientist at Fiverr
For me, the most important aspect of the program is the industry project. There's nothing like working on a real problem with experts in the field. I feel that the classes prepared me well for this kind of hands-on data science work. In particular, the variety of lecturers from tech and academia is definitely an advantage of the program.
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 algorithms. 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.
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.
Team

Our Team

Team page
Elena Bunina
Professor, Department of Mathematics, Bar Ilan University
Read More
Y-DATA Scientific Advisor
Dr. Inbar Huberman
PhD from The Hebrew University of Jerusalem
Read More
Lecturer at Deep Learning & GenAI Hand on Applications course
Karin Brisker
Data Scientist at Microsoft Israel
Read More
Lecturer at Deep Learning & GenAI Hand on Applications course
Kosta Rozen
Product Analytics Team Lead at Google
Read More
Lecturer at Python for Data Processing course
Lior Sidi
Co-Founder & CTO at stealth startup
Read More
Lecturer at Classical ML course
Noa Lubin
Director of Data Science at Fido
Read More
Lecturer at Classical ML course
Dr. Omri Allouche
Head of Research at Gong.io, Data Scientist and Lecturer
Read More
Lecturer at Deep Learning & GenAI Foundation course
Segev Arbiv
Principal Data Scientist at SimilarWeb, Mentor and Lecturer
Read More
Lecturer at Classical ML course
Dr. Tomer Gazit
Data Science Team Lead at Hello Heart
Read More
Lecturer at Probability & Statistics
Serj Smorodinsky
Data Science Team Lead at Loris.ai
Read More
Lecturer at Data Science in Production course
Kosta Rozen
Product Analytics Lead at Waze
Lecturer at Python for Data Processing course
Partners

Our Partners

The Association of Engineers, Architects and Graduates in Technological Sciences in Israel
Intro to DS course in partnership with AEAI.
College of Management Academic Studies
Academic courses to MBA students in the field of data science by Y-DATA.
Nebius
Is a leading AI-centric public cloud platform designed to support the entire machine learning lifecycle.
Tel Aviv University
Partnership with Blavatnik school of Computer Science.
Helmholtz Information & Data Science Academy
HIDA connects and serves as the roof to 6 newly founded data science research schools linked by a network of 14 national research centers and 17 top-tier universities across Germany.
Amazon Web Services
AWS credits for Y-DATA students.
popular questions

FAQ

Can I apply for just one program, or do I have to join the full bundle?
How does the application process work?
What level of math knowledge is expected from the candidates?
What level of statistics and probability knowledge is expected from the candidates?
What level of coding skills is required to enter the program? Do you require knowledge of specific languages?
Can I apply with zero coding experience?
What is the time commitment for this program? Can I combine it with work or academic studies?
What is the cost of the program?
What is the language of the program?
Where are the courses taking place?
Still have any questions?
Powered by Nebius
Nebius, established in late 2023, is a leading AI-centric public cloud platform designed to support the entire machine learning lifecycle. With a focus on empowering ML practitioners, Nebius offers comprehensive infrastructure and aims to become the preferred platform for generative AI developers.
Kosta Rozen
Product Analytics Lead at Waze
Lecturer at Python for Data Processing course