Preliminary Course Schedule 2018
There are two weekly lectures: wednesday 15.1517.00 hrs and friday 9.0010.45 hrs. Furthermore, there are computer lab sessions in which we practice with R, and work on the practical assignments. These sessions take place on wednesday 17.1519.00 hrs. In the schedule below, lecture 38A is the lecture on wednesday in week 38, 40B is the lecture on friday in week 40, and 43C is the computer lab session in week 43. Some of the lecture timeslots will be used for solving exercises. These timeslots are indicated in green in the schedule below. Working on these exercises is good practice for the written exam.
The first lecture is on friday, september 7th.
The first computer lab session is on wednesday, september 12th.
Before the lecture, the links are to last year's slides. The slides that are posted after the lecture may contain some minor updates. Important updates will be noted in the schedule.
Lecture  Subject/Slides  Literature 

36A  No Lectures (Master Introduction)  
36B  Introduction and Overview  A. Feelders et al.: Methodological and Practical Aspects of Data Mining 
37A  Classification Trees (1)  Lecture Notes on Classification Trees Chapter 8 of Book ISLR 
37C  Computer Lab: Introduction to R Work on assignment 1 

37B  Classification Trees (2)  Lecture Notes on Classification Trees Chapter 8 of Book ISLR 
38A  Classification Trees: Exercises (Solutions).  
38C  Computer Lab: Work on assignment 1  
38B  Bagging and Random Forests Some proofs 
Chapter 8 of Book ISLR 
39A  Undirected Graphical Models (1)  Lecture Notes on Graphical Models 
39C  Computer Lab: Work on assignment 1  
39B  Undirected Graphical Models (2)  Lecture Notes on Graphical Models 
40A  Undirected Graphical Models: Exercises.  
40C  Computer Lab: Work on assignment 1  
40B  Frequent Pattern Mining (1)  Lecture Notes on Frequent Item Set Mining 
41A  Frequent Pattern Mining (2)  
41C  Computer Lab: Work on assignment 1  
41B  Frequent Pattern Mining: Exercises.  
42A  Text Mining (1): Naive Bayes  Chapter 4 of Jurafsky and Martin 
42C  Computer Lab: Work on assignment 2  
42B  Text Mining (2): Logistic Regression (Updated on 20102017). 
Chapter 5 of Jurafsky and Martin 
43A  Bayesian Networks (1)  Lecture Notes on Bayesian Networks 
43C  Computer Lab: Work on assignment 2  
43B  Bayesian Networks (2)  Lecture Notes on Bayesian Networks Exercises. 
44A  Social Network Mining  Article Lu and Getoor 
44C  Computer Lab: Work on assignment 2  
44B  Active Learning (Guest Lecture by Georg Krempl) 
TBA 
45  Written Exam 