Self-paced mlcourse.ai

Website

The website mlcourse.ai is completely redesigned.

Now, all course materials are published as a Jupyter book – an executable book containing markdown, code, images, graphs, etc. A strong advantage of this type of content is that it’s actually a book with executable content meaning that the pages that you see are not just static but are updated with each build of the book by running all Python code. We describe Jupyter books in more detail here.

Prerequisites

The prerequisites section is updated to include Python and math courses, and tools used in the course: git, bash, Docker, Jupyter Notebooks, etc.

Main content

There are 10 topics in the course – from exploratory data analysis with Pandas to gradient boosting. For each topic, there’s an introductory part (here’s an example for Topic 1) that lists articles to read, lectures to watch, and assignments to crack when you're passing the course in a self-paced mode.

Bonus assignments

Additionally, you can purchase a Bonus Assignments pack with the best non-demo versions of mlcourse.ai assignments if you select the “Bonus Assignments” tier. The bonus pack contains 10 assignments, in some of them you are challenged to beat a baseline in a Kaggle competition under thorough guidance (“Alice” and “Medium”) or implement an algorithm from scratch – efficient stochastic gradient descent classifier and gradient boosting.