MegaData: Federated Machine Learning
MegaData: Federated Machine Learning

MegaData: Federated Machine Learning

On-site in Tartu 31 July - 11 August 2023

This course provides an introduction to Federated Machine Learning (FL), a privacy-preserving distributed ML. The course will cover the foundational aspects of FL operation and deployment models in Edge computing. Modern FL technologies will cover various aspects, including different data distributions, aggregation algorithms, and communication efficiency approaches. The students will be introduced to state-of-the-art FL technologies and architectures and guided to investigate novel ideas in the area via lectures, practice sessions, and projects. We will also look at industry trends and discuss some innovations that have recently been developed.

The course targets MSc degree students and Ph.D. candidates looking to develop their capacity in modern computer deployment architecture at the Edge/Fog to meet the increasing demand in industry and academia. Also, the course is designed for students of joint data science and distributed system curriculum towards Edge Intelligence. We combine theory, practice sessions, and project assignments to learn about FL. After completing this course, you will learn more about designing and developing an FL solution. Some course material will be drawn from research papers, industry white papers, and technical reports.

The course can be taken on-site in Tartu, Estonia. We have a lecture and discussions in the morning session. Afternoon sessions are dedicated to practicing sessions and project work.

During 18-20 September 2023 the 1st International Symposium on Federated Learning Technologies and Applications (FLCon) takes place in Tartu. The student of this course have the opportunity to publish their projects done during the course in the symposium.

Focus area: Designing and Implementing Federated Machine Learning Coordinating unit at UT

Institute of Computer Science (Data Systems Group)

Study Field: Computer Science Course Leader Feras Awaysheh
Format Hands-on workshop Location Tartu, Estonia, Delta Centre
Course dates: 31 July - 11 August 2023 Apply by: 30 April 2023
ECTS: 3 (+2 for additional assignment) Fee: 650 EUR
Study MSc/PhD Language English


  • Feras Awaysheh, University of Tartu, Estonia
  • Sadi AlAwadi, Halmstad University, Sweden

Guest Talks:

  • Afsana Khan, Maastricht University, Netherlands.  
  • Daniel J. Beutel, Cambridge University, UK  
  • Florian van Daalen, University Maastricht, Netherlands 
  • Mohamed Elmahallawy, Missouri University of Science and Technology, USA 
  • William Lindskog, Technical University of Munich, Germany 
  • Salman Toor, Uppsala University, Sweden  
  • Hossam Fakhory, Petra University, Jordan  
  • Hassan Eldeeb, Tartu University, Estonia  


Application is closed.


Two weeks prior to the start of the programme an information file will be sent to all participants. This file contains the daily schedule and relevant contact information of the programme managers.

Students are responsible for their travel, accommodation and travel insurance (visa arrangements if needed) from their home country to Tartu and back to their home country. It is recommended to visit the Tartu Welcome Centre website and arrival and housing section to find accommodation opportunities.


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