During the course, 10 exercise sessions are offered. For most topics, there is both a pen-and-paper session (pp) and a computer session (c). Each session is offered at two different time slots in the schedule. We hope that the students will be evenly distributed among the sessions, but you can choose which session to attend. There are two exercise sessions in parallel, split between two teaching assistants: one on campus and one on zoom. Use the course zoom link to reach the zoom sessions.

During each exercise session, the teacher will present a summary of the material covering the specific topic, after which you are expected to work on the problems on your own. We recommend attempting to solve the problems beforehand, and taking the opportunity to ask questions and discuss the problems with the teacher and your fellow students during the exercise sessions. A few of the problems are listed as recommended, but we encourage you to read and reflect upon all problems (even if you do not solve them).

Use this document to queue for help during the zoom exercise sessions.

#	Topic	Material	Recommended problems	Additional problems
1.	Linear Regression (pp)	Session1.pdf	1, 2, 3	4, 5
2.	Linear Regression (c)	Notebook Solutions Open in colab	1, 2, 3, 4	5
3.	Logistic Regression, LDA, QDA, kNN (pp)	Session3.pdf Session3 - Recap + solutions	1, 2, 3, 5	4, 6, 7
4.	Logistic Regression, LDA, QDA, kNN (c)	Notebook Solutions Open in colab Ex. 4.1 from the live coding session	1, 2, 3, 4	5
5.	Bias and variance, model selection, cross validation (pp)	Session5.pdf Session5 - Recap + solutions	1, 2, 3, 4	5, 6
6.	Bias and variance, model selection, cross validation (c)	Notebook Solutions Open in colab	1, 2, 3	4
7.	Tree-based methods (pp)	Session7.pdf	1, 2, 3, 4
8.	Tree-based methods (c)	Notebook Solutions Open in colab Extra material on bootstrapping	1, 2	3
9.	Boosting (c)	Notebook Solutions Open in colab	1, 2, 3	4, 5
10.	Neural Networks (pp)	Session10.pdf Detailed solutions to 2 & 4 Session10 Recap + Solutions	1, 2, 3, 4

pp = pen and paper, c = computer