Learn. Practice. Launch.
Start your professional journey in Applied Data Science with Y-DATA
Applications for the Y-DATA Program 2023-24 are closed
Highlights
Next class start:
Industry Projects:
Workload:
Tuition Fee:
Where:
Schedule:
October 2023
Real projects by top companies
20-25 weekly hours
29k ILS (Or apply for success-based education*)
Tel Aviv
Tuesday 17:00-21:00, Friday 9:00-13:00
About
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 will we provide
What will you get
250 hours of intensive
in-person training
Practical experience with full cycle data science industry project
Real-world industry project for your portfolio
Fluency in Python and its relevant tools (scikit-learn, pandas, matplotlib, numpy)
Dedicated career center and soft-skills workshops tailored to industry needs
Extensive experience in neural networks and their applications in NLP and computer vision, including recent developments
Access to cloud computation resources
Practice in reading scientific papers and presentation of papers and ongoing research
Networking and more - ongoing involvement with a community of experts
Certificate of completion
Y-DATA offers a unique combination of advantages not found in other programs
In-depth understanding of theoretical foundations
Online courses
Offline courses
Advanced degree
Y-DATA
Experience working on practical, real-world challenges
No upfront cost: option to pay only once employed in the field
Introduction to current research and advances
Thorough candidate screening process
Time commitment compatible with working in parallel
Experienced
Industry mentors
Access to computational cloud resources for all your projects
Y-DATA vs Online courses
In-depth understanding of theoretical foundations
Experience working on practical, real-world challenges
No upfront cost: option to pay only once employed in the field
Introduction to current research and advances
Thorough candidate screening process
Time commitment compatible with working in parallel
ExperiencedIndustry mentors
Access to computational cloud resources for all your projects
Y-DATA vs Offline courses
In-depth understanding of theoretical foundations
Experience working on practical, real-world challenges
No upfront cost: option to pay only once employed in the field
Introduction to current research and advances
Thorough candidate screening process
Time commitment compatible with working in parallel
ExperiencedIndustry mentors
Access to computational cloud resources for all your projects
Y-DATA vs Advanced degree
In-depth understanding of theoretical foundations
Experience working on practical, real-world challenges
No upfront cost: option to pay only once employed in the field
Introduction to current research and advances
Thorough candidate screening process
Time commitment compatible with working in parallel
ExperiencedIndustry mentors
Access to computational cloud resources for all your projects
Our Team
Admission process
01
02
03
Application
Test
Interview
Submit the application filling the form
Take an online test assessing your analytical and basic programming skills
Tell us more about your background, experiences, and interests, as well as your motivation and goals for the program. Few technical questions might be asked during the interview
FAQ
Still have any questions?
Alumni quotes
Yechiel Levy
Rachel Shalom
Ido Nissim
CTO at OptimalQ
Data Scientist at Owlytics
Data Engineer at AllCloud
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.
I realized that as a product manager in a travel tech startup, I needed heavy tools to analyse data, do predictions and more. So I started checking all kind of data science boot camps, 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.
I think the very best thing about the course are 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, worked as groups, that 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.
Arseny Levin
Liad Yosef
Tal Ben-Yehuda Heletz
Lior Tabori
Nir Aviv
Jonathan Ohnona
Andrey Nikitin
Amit Alon
Fraud Detection Lead at DoubleVerify
Client Architect at Duda
Deep Learning researcher at Trigo
Data Scientist at Agoda
Software Engineer and Data Scientist at Fiverr
Data Scientist at eToro
Data Scientist at Wix
Data Scientist at KHealth
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.
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, let me explore and widen the area of my thoughts.
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.
I wanted to get into this 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.
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.
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.
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 masters 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 that gap.
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 anything 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.