Open Machine Learning Course is an open Machine Learning course by OpenDataScience. The course is designed to perfectly balance theory and practice. You can take part in several Kaggle Inclass competitions held during the course.

Current session: February 11th - April 26th, 2019. You can join at any point.

How to start with the course:

  • set up a local or cloud Jupyter environment (Anaconda, Kaggle Kernels, Google Colab etc):
  • go to and download a Jupyter notebook (click an nbviewer link -> download icon in the upper-right corner -> right click -> Save link as), further instructions are given therein (alternatively, you can pull changes from the course repo if you’re familiar with git)
  • run the notebook with Jupyter, read instructions carefully, there’ll be ample links to corresponding materials within our course (lectures, articles, demo assignments)
  • fill in the missing Python code, finally you’ll be asked to fill in a Google quiz form. In some assignments, you’ll be asked to make a submission in a Kaggle Inclass competition. You need to do it before the deadline

How to join ODS Slack community:

  • fill in this form, you’ll get an invitation (check your spam folder), you’ll be able to login to, check FAQ in case of problems
  • when in Slack, first check the #mlcourse_ai_news channel for latest announcements, then you can freely chat in the #mlcourse_ai channel, but use threads and check pinned items first (these are described in an introductory e-mail that you’ll get)
  • stick to special threads (mentioned in assignments) for questions on assignments

Navigating this site:

  • on this page, you’ll find the main course content, see icons below
  • video - video recordings of fall 2018 lectures
  • prerequisites - what you need to join this course
  • roadmap - plan for the ongoing course session
  • assignments - links to ccurrent assignments and demo version for practice
  • tutorials - tutorials written be course participants
  • resources - a list of all materials constituting the course
  • rating - current rating and top-performers of previous sessions
  • FAQ - Frequently Asked Questions
  • contacts - how to reach the course team
  • contrib - how you can help