Advanced Machine Learning


Event period Explanation of the participation options

In future

Currently 10 places available
Courses of this module
F4 Advanced Machine Learning
Product information "Advanced Machine Learning"

In this module you will learn selected and advanced machine learning methods and problems, such as:

  • Probabilistic graphical models (modeling and inference)
  • Structured (sequential) problems
  • Selected topics according to the current state of research, such as Gaussian Processes, Reinforcement Learning and Mixture Models

is restricted access: Yes
Requirements - university entrance qualification: Not required
Requirements - one year of work experience: Not required
Requirements Language: None
Requirements Expertise: None
Other requirements

  • Participation in the modules "DS-F1 Mathematik & Statistik" as well as "DS-F2 Grundlagen des maschinellen Lernens" or proof of corresponding knowledge
  • Mastery of a programming language (e.g. Python)

Topic: IT & Digitalisation
Format of course: Blended Learning
Level: Master
Course language: English
Study programme: Data Science
Number of credit points / ECTS: 5
Workload Contact time (in hours): 30
Workload self-study time (in hours): 95
Examination: inter-course examination (Module exam)
Exam format: Term paper
Further exam format: No further Exam

  • Acquire specialized knowledge in the field of machine learning
  • Acquire the ability to independently design machine learning algorithms for a given task
  • Implement learning algorithms and evaluate their results

27 = Dates of this module
27 = Dates with overlap
27 = Modules already selected
Please note: Dates subject to change