by Pavel Kuptsov for HSE University, Nizhny Novgorod, Russia

1. Brief review of Python
2. Visualization of data
3. Linear algebra
4. Statistics
5. Probability
6. Hypothesis and inference
7. Gradient descent
8. Getting data
9. Working with data
10. Dimension reduction
11. Basic concepts of machine learning
12. k-nearest neighbors
13. Naive Bayes classification
14. Neural networks and deep learning
15. Image recognition
16. Vector models of text
17. Deep networks for natural language processing