Course Schedule 2026

There are two lectures per week, on Tuesday and Thursday, and there is one tutorial session per week after the lecture on Thursday. During the weekly tutorial sessions you can work on practice exercises and the practical assignment. There is no tutorial session in week 37. Please consult My Timetable for the times and locations of the lectures and tutorial sessions. In the schedule below, lecture 38A is the lecture on Tuesday in week 38, 40B is the lecture on Thursday in week 40, 43C is the tutorial session in week 43, and 42D is a deadline in week 42. All deadlines are on Friday.

Currently, last year's slides are online; they will possibly be updated shortly before or after the lecture.

Lecture Subject/Slides Literature Deadlines
37B Introduction and Overview    
38A Classification and Regression Trees (1) Lecture notes on classification trees
Chapter 8 of Book ISLR
 
38B Classification and Regression Trees (2) Lecture notes on classification trees
Chapter 8 of Book ISLR
 
38C Work on exercises    
39A Tree Ensembles
Some small proofs
Lecture notes on classification trees
Chapter 8 of Book ISLR
 
39B Text Mining (1) Jurafsky and Martin,
Appendix B
 
39C Work on exercises    
39D Homework 1   Friday, September 25th
40A Text Mining (2) Jurafsky and Martin,
Chapter 4
 
40B Undirected Graphical Models (1)
Log-Linear Expansion Example
Lecture notes on graphical models  
40C Work on exercises/assignment    
41A Undirected Graphical Models (2)
Counting u-terms
Lecture notes on graphical models  
41B Undirected Graphical Models (continued)    
41C Work on exercises/assignment    
41D Homework 2   Friday, October 9th
42A Frequent Pattern Mining Lecture Notes on Frequent Item Set Mining  
42B Bayesian Networks (1) Lecture Notes on Bayesian Networks  
42C Work on exercises/assignment    
42D Homework 3   Friday, October 16th
43A Bayesian Networks (2) Lecture Notes on Bayesian Networks  
43B Social Network Mining: Link Prediction Articles Liben-Nowell and Kleinberg/El Hasan et al.  
43C Work on exercises/assignment    
43D Assignment   Friday, October 23rd
44A PAC Learning and the VC dimension (1)    
44B PAC Learning and the VC dimension (2)    
44C Work on exercises    
44D Homework 4   Friday, October 30th
45A TBD    
45B Q & A Session    
45C Work on exercises    
46 Digital Exam in Remindo