Module Number ML4202 
Module Title Probabilistic Machine Learning (Probabilistic Inference and Learning) 
Lecture Type(s) Lecture, Tutorial 

ECTS  9  
Work load  Contact time  Self study 
Workload:
270 h Class time:
90 h / 6 SWS Self study:
180 h 

Duration  1 Semester  
Frequency  In the summer semester  
Language of instruction  English  
Type of Exam  Written exam (in case of a small number of participants: oral tests) 

Content  Probabilistic inference is a foundation of scientific reasoning, statistics, and 

Objectives  Students gain an intuitive, as well as a mathematical and algorithmic understanding 

Allocation of credits / grading 
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Lecture
V
o
4
6.0
wt
90
g
100
Tutorial
Ü
o
2
3.0


Prerequisite for participation  ML4101 Mathematics for Machine Learning  
Lecturer / Other  Hennig, Macke  
Literature  Literature will be listed at the beginning of the semester. / Standard undergraduate knowledge of mathematics is required, to the extent 

Last offered  Sommersemester 2022  
Planned for  Sommersemester 2024  
Assigned Study Areas  INFOINFO, INFOPRAK, INFOTHEO, MEDIAPPL, MEDIINFO, MLCS, MLDIV, MLFOUND 