Start your professional journey
in Applied Data Science with Y-DATA
Application for the classes in 2023-24 is open.
Next class
weekly hours
Tuesdays and Fridays
Real projects by top companies
Frontal studies in Tel-Aviv
What is 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.
What do we offer:
250 hours
Real projects
5 years
of intensive in-person teaching
Real-world industry project for your portfolio
employed in top tech companies
Over 5 years’ proven experience in Israel
employement rate in DS/ML positions
Who is this for?
looking to specialise in DS
Tech professionals
looking to get started in the industry
Advanced degree graduates
Data professionals
looking to advance their career
Background and Requirements
Degree requirements
background requirements
Academic STEM degree
- OR -
Proficiency with at least one programming language
Fluency in English
At least one free weekday for coursework
Advanced degree in any field
Our Alumni
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.
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 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.
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.
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 couldn't have done before, and let me explore and widen the area of my thoughts.
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.
Nir Aviv
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.
Software Engineer and Data Scientist at Fiverr
Lior Tabori
Data Scientist at Agoda
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
Data Scientist at Owlytics
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
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.
Data Scientist at KHealth
Our Team
Segev Arbiv
Principal Data Scientist at SimilarWeb, Mentor and Lecturer
Anna Lapidus
Data Scientist and researcher
Efrat Egozi
Data science consultant and ML expert
Ekaterina Artemova
Post doctoral researcher at MaiNLP Research Lab @CIS LMU
Adir Solomon
ML Researcher
Omri Allouche
Head of Research at Gong.io, Data Scientist and Lecturer
Niv Haim
Machine Learning researcher at the Weizmann Institute of Science
Anatoly Bard
Software Developer at Revolut, Lecturer at HSE
Daniel Nevo
Senior Lecturer at the Department of Statistics at Tel Aviv University
Noa Lubin
Director of Data Science at Fido
Yuval Belfer
Developer Advocate at AI21 Labs
Rachel Buchuk
Statistics and Operations Researcher at the Hebrew University
Inbar Huberman
PhD from The Hebrew University of Jerusalem
Yury Mokrii
AI Researcher
Guy Shtar
Machine Learning Expert at Salesforce
Guy Uziel
Co-founder and CTO of Litigate
Lior Sidi
Senior Data Scientist at Wix
Ronen Tal-Botzer
PhD in AI, CEO at Evolution.inc
Our Partners
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.
Online Test
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.
Take an online test assessing your analytical and programming skills
Next online tests will take place in July-August 2023.
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.
July - August
August - September
Y-DATA structure
Y-DATA is taught in-person, on campus. Our courses are streamed live and recorded, but we believe there is no match to in-class discussion and coffee-break networking.
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.
Research Seminars
Choose one of the real‑life data projects offered by our industry partners, and work on it throughout the year. You will receive guidance through weekly meetings with experienced industry mentors provided by us, as well as periodic meetings with the project’s data owner.
Study specific topics in data analysis and machine learning in short, dedicated courses (4‑12 weeks each), covering topics across all the range from ML foundations to advanced, state‑of‑the-art applications. All the courses are taught in an applicative and hands-on manner and include extensive practice.
Become familiar with the current scientific research and advancements through research seminars, where you will also engage in in‑depth discussions and exploration of the most recent advancements in the field.
Study Curriculum
Python for Data Processing
Probability Theory and Statistics for Data Science
Supervised Learning
Unsupervised Learning
Deep Learning
Elective courses in advanced topics:
Generative AI
Dialog systems
Full syllabus
Applications & Admission Process
Time Commitment
Program Information
When & where
Industry Projects
Still have any questions?