Preliminary Course Schedule 2018

There are two weekly lectures: wednesday 15.15-17.00 hrs and friday 9.00-10.45 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 17.15-19.00 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 20-10-2017).
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