Community
We invest our resources into courses, workshops and meetups for all levels of professionals: from people with no tech experience seeking to start their way in the field, to seasoned data scientists and engineers looking to deepen their knowledge of advanced topics. We believe in "paying it forward" and build our community accordingly, so most of our initiatives are free of charge or use success-based tuition criteria.
Y-DATA is more than just a single training program - it is an environment in which data professionals can grow.
Our commitment is to the community of data-related professionals as a whole, its development and enrichment.
Our past events
Yet another Gradient Boosting
Opening Event
Under the Hood
Large-Scale Recommender Systems
Selection Bias and Casual Inference
Computer Vision - Smarter, Faster, Better
Spring 2019
ML in Cybersecurity: two sides of a coin
Opening event
Courses and events
Community courses
Causal Inference
Lecturer:
Daniel Nevo
It is well known that correlation does not imply causation. However, often the main interest lies in the impact of an intervention. Furthermore, with the increase in the amounts of data collected, issues concerning systematic bias become more and more important in modern data science. In this course, we will first define what causal effects are, and then present a reservoir of causal inference methods to estimate these effects accompanied by real-life examples. We will also learn about basic terms as confounding and selection bias, and how to identify their potential presence and adapt our analysis plan using directed acyclic graphs.
Advanced Time Series
Lecturer:
Gleb Ivashkevich
The course is dedicated to deep learning techniques in time series modelling. Deep learning models offer significant advantages when applied to time series problems, regardless of the task (regression, classification, etc). The course is centered around a set of seminal research papers, several datasets and known use cases. Since there exists no well-established curriculum in the domain of deep learning for time series, we'll use this unique structure to bring together academic innovation and industry experience.
Adversarial learning
Lecturer:
Ziv Katzir
Adversarial machine learning (AL) is a relatively new and extremely active research domain, focused on understanding the susceptibility of machine learning algorithms to misleading inputs.This course is a journey through the evolution of adversarial machine learning in recent years. It starts with the early methods of attack and defense, and concludes with recent discoveries and outstanding research questions. As part of this journey we will review notable studies, and discuss their contribution to the understanding of this phenomenon.
Practical crowdsourcing for efficient ML
The course is dedicated to crowdsourcing as a tool for efficient and scalable data labeling. Great amounts of data are essential for most AI-based technologies. The better the algorithms are, the more data is needed to make more of them. This is the reason why efficient data labeling is a demanded yet essential skill for professionals dealing with ML. Crowdsourcing helps to establish robust and scalable data labeling processes by distributing tasks among a vast cloud of users.
Community courses
Data Analyst
Starting Date: 13.04.2023
Collect, analyze and visualize data. Over the course of this 7-month program, you will master the skills required to become a data analyst and build a portfolio of projects on topics such as these: User preferences for streaming on-demand media, the effect of weather on taxi services and boosting e-commerce revenue.
Data Skills
Intro to Data Science
Starting Date: 13.04.2023
This course aims to provide an opening to the world of Data Science by offering an entry-level perspective on a wide range of DS and ML topics. The course provides an introduction and hands-on experience with multiple common DS tools, as well as understanding of core concepts of modelling and working with data. Over the course of 6 weeks, Intro to DS course will provide practical experience and understanding of core ML tasks such as classification, regression, and clustering, as well as overview of the capabilities of Deep Learning and state-of-the-art developments. The course lays the groundwork for anyone interested in the field or looking to get started by introducing and exploring the fundamental concepts behind data science and the data industry.
Academic courses

Data is quickly becoming our world’s most valuable commodity. As its importance grows, it’s never been more important to explore, understand and communicate data concepts as part of one’s daily work. This course offers the necessary tools to use data to its full potential and to obtain insights needed from the position of a product manager. The course covers 4 separate modules across 3 verticals: product, management, and data science.

Lecturer:
Adir Solomon
Course at the College of Management
meetups
Understanding the Junior Paradox
Date: 25.05.2022 | 6:30 pm
What is stopping juniors from getting jobs and gaining experience? Why are employers stuck without candidates? How does it look from a tech employer's perspective? What opportunities are within this situation? Welcome to the Junior Paradox.
Y-DATA#21: Training Data—The Overlooked Area of Modern AI
Date: 25.05.2022 | 6:30 pm
The era of modern AI started with the rise of big data. Once you have large amounts of logged structured data, be it clicks on the products in an online store, or time spent on a certain webpage in a browser, or percentage of paid credits in a bank, data science steps in. However, in reality, the data is often either not structured or, even worse, does not exist at all. For example, a voice assistant will only learn to correctly activate after the model analyses thousands of hours of speech recordings made by different voices, accents, amidst surrounding noises. Further, a search engine will only learn how to rank the most relevant sites on top after “seeing” millions of pairs matching user queries and web pages documents, judged by the relevance of the match. All the magic and power of artificial intelligence has a natural glass ceiling. And this ceiling is training data.

Y-DATA#19: DS career paths: advancing beyond your first role

Date: 23.06.2022 | 6:30 pm

As more and more data professionals are reaching this career milestone, with a few years of industry experience as data scientists and looking for the next step, we invite you to join this meetup to take a look at varied perspectives on the subject. We'll feature a panel discussion by a team of talented industry insiders, who come from different backgrounds and are taking different trajectories into the future.

Y-DATA#18: ML Methods for Video Analysis

Date: 17.03.2021 | 6:00 pm
Two great talks about video analysis in real life and recent ML methods used in this field. Our speakers will be Alex Rav-Acha (VP Engineering at Vimeo) and Sergey Ovcharenko (Yandex).