Machine Learning 2026/27 fall

Before the practice sessions

In practice sessions we will be working in Google Colab and Python 3. Ideally, familiarize yourself with NumPy, Pandas, and Google Colab before the practice sessions.

Zoom links for online participation and Colab notebooks

Group #	Instructor	Room	Zoom room	Google Drive
Group 1	Dmytro	1008	(log into courses to see link)	(log into courses to see link)
Group 2	Kati	2010	(log into courses to see link)	TBA
Group 3	Ali	2034	(log into courses to see link)	TBA
Group 4	Taavi	1008	(log into courses to see link)	drive
Group 5	Taavi	1008	(log into courses to see link)	drive
Group 6	Dzvinka	2010	(log into courses to see link)	TBA

We recommend attending practice sessions in person. Nevertheless, there is always an option to attend some practice sessions remotely.

Practice session schedule

The following schedule is subject to change. Keep an eye on our Slack channel for updates!

Practice #	Date	Title	Recording
Practice 01	September 7–9	Supervised learning (part I)	TBA
Practice 02	September 14–16	Supervised learning (part II)	TBA
Practice 03	September 21–23	Unsupervised learning (part I)	TBA
Practice 04	September 28–30	Unsupervised learning (part II)	TBA
Practice 05	October 5–7	Deep learning (part I)	TBA
Practice 06	October 12–14	Deep learning (part II)	TBA
Practice 07	October 19–21	Regularisation methods	TBA
Practice 08	October 26–28	Deep Learning HW reversed	TBA
Practice 09	November 2–4	Ensemble learning (part I)	TBA
Practice 10	November 9–11	Ensemble learning (part II)	TBA
Practice 11	November 16–18	Intermediate project presentations
Practice 12	November 23–25	Performance metrics	TBA
Practice 13	November 30–December 2	Project consultations
Practice 14	December 7–9	No practice session (guest lecture)
Practice 15	December 14–16	Final project presentations