Learn Practice Launch

2025 Oct
Next Class
20-25
Weekly hours [workload]
Tue and Fri
Schedule
29,000
NIS Tuition [discount options available]
Frontal studies in Tel‑Aviv
Format
Real projects by top companies
Practice
ABOUT

What is Y-DATA

Y-DATA is an intensive one-year career advancement program in data science
It 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.
Learn more
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
6
years
6 years
Over 6 years’ proven
experience in Israel
250+ graduates
250+ 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
Networking and more
Networking and more
ongoing involvement with
a community of experts
OUR PROJECTS
Industry projects
Full project catalog
Web Technology
Detection
Finding Genes with Similar Functional Homology
Text Classification Modeling Improvements
Dynamic Range Prediction for Vehicles
Diastole/Systole
Indetification in ECG
Wix Restaurants
Segmentation
LLM Agent-Managed Interface for Business Monitoring
Detecting Faulty Sensor
Data
Hourly Demand
Prediction
Product Clustering
and Fraud Risk Assessment
Oral Anomaly Detection
Botnets Site Clustering
Multi-domain Digital Pathology Stain Style Transfer
Classification and Prediction of Epileptic Activity in EEG
Multi-domain digital pathology styletransfer
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
+16 more projects
admission scheme

Admission process

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.
Learn more about Admission
01
Application
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. Next online tests will take place in July-August 2025.
July - August 2025
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.
August - September 2025
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

Eden Shochat
Equal Partner at Aleph
Elena Bunina
Professor, Department of Mathematics, Bar Ilan University
Y-DATA Scientific Advisor
Ira Cohen
Co-Founder, Chief Data Scientist at Anodot
Kira Radinsky
ChairWoman & Chief Technology Officer at Diagnostic Robotics
Lior Rokach
Professor of software and information systems at Ben-Gurion University
Daniel Nevo
Senior Lecturer at the Department of Statistics at Tel Aviv University
Lecturer at Causal Inference course
Guy Shtar
Machine Learning Expert at Salesforce
Lecturer in Unsupervised Learning course
Inbar Huberman
PhD from The Hebrew University of Jerusalem
Lecturer at Deep Learning course
Karin Brisker
Data Scientist at Microsoft Israel
Lecturer at ML foundations
Kosta Rozen
Product Analytics Lead at Waze
Lecturer at Python for Data Processing course
Lior Sidi
Senior Data Scientist at Wix
Lecturer at Supervised Learning course
Niv Haim
Machine Learning researcher at the Weizmann Institute of Science
Lecturer at Generative AI course
Noa Lubin
Director of Data Science at Fido
Lecturer in Supervised Learning course
Omri Allouche
Head of Research at Gong.io, Data Scientist and Lecturer
Lecturer at Deep Learning course
Oren Elisha
Data science manager at Forter
Lecturer at ML foundations
Rachel Buchuk
Statistician at SZMC
Lecturer at Probability Theory and Statistics for Data Science
Segev Arbiv
Principal Data Scientist at SimilarWeb, Mentor and Lecturer
Lecturer at Unsupervised Learning course
Shaul Solomon
Lead Data Scientist at DockTech
Lecturer at Probability & Statistics
Shuki Cohen
Data Scientist at AI21 Labs
Guest Lecturer
Talia Tron
Data Scientist & NLP researcher @ K-Health
Lecturer at project workshops
Yoel Zeldis
Algorithm Developer
Lecturer at ML Tools and Applications
Yuval Belfer
Developer Advocate at AI21 Labs
Lecturer at Generative AI course
Dina Bavli
Data Scientist & consultant
Project mentor
Efrat Egozi-Levi
Data science consultant and ML expert
Project mentor
Ishai Rosenberg
Co-Founder and CTO
Lecturer at MLops course
Maya Malamud
Senior Data Scientist and Researcher at Timna
Project mentor
Moshe Mash
AI researcher
Project mentor
Netta Lieber
Data Science Team Leader
Project mentor
Nir Ben Zvi
Deep Learning and Computer Vision Consultant
Project mentor
Shani Kotler
Data / AI Consultant
Project mentor
Tom Haramaty
Machine Learning Consultant
Project mentor
Tomer Ahrak
Data Science Researcher at Neosec
Project mentor
Yair Meidan
Data Scientist / Applied ML Researcher
Project mentor
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

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