What you will learn

  • How Machine Learning works, its possibilities, its limitations, and the importance of data
  • How to create, evaluate and deploy predictive models, via open source libraries, APIs and ML-as-a-Service platforms
  • How to formulate ML problems that create value from data and that power predictive applications with innovative features

See workshop agenda for more details.

Great mix between lectures, hands-on work and Q&A. Everyone in the team was really glad they came!
— Nicolas Schwartz, Tech Lead at BlaBlaCar
 

Prerequisites

  • Experience in programming and with the command line
  • Attendees are expected to bring their own laptops for the hands-on practical work
  • Basic knowledge of calculus, linear algebra, and probability theory will be useful for Theory in Modules 2, 4, 5 (see agenda)

Target audience

This course is targeted to hackers, developers, software engineers and CTOs who are beginners in machine learning.

Each workshop will be given in a classroom setting with up to 20 participants.
Join now to avoid missing out!