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Advanced Machine Learning

Maschinelles Lernen Weiterbildung im Modulstudium

€1,930.00

Participation Explanation of the participation options
Event period
Certificate programme

In the certificate programme, you take modules worth at least 15 credit points, you are enrolled as a student at Leuphana University of Lüneburg, you have access to all the university's resources, you take examinations and you receive the university certificate "PS Individuale" as your degree.

More information on the Certificate Programme

Module studies

You complete the module studies with an examination and receive the specified credit points. These can be credited towards a Bachelor's or Master's degree. The modular study programme is interesting for you if you only want to book a single module. At the end, you will receive a certificate with a detailed list of your achievements.

More information on Module Studies

Module participation

Participation in the module takes place WITHOUT an examination. You do not receive any credit points. Credit points are important if you want to have them credited towards a Bachelor's or Master's degree. You will receive a certificate of attendance at the end of the module.

More information on Module Participation

Currently 10 places available
Courses of this module
F4 Advanced Machine Learning
First date Friday, 04.04.2025 at 14:30 o'clock → Last date Saturday, 13.09.2025 at 10:00 o'clock
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: No
Requirements - university entrance qualification: Not required
Requirements - one year of work experience: Not required
Requirements Language: None
Requirements Expertise: None
Other requirements

Recommendation:
  • Participation in the modules "DS-F1 MathematiK & Statistik" as well as "DS-F2 Grundlagen des maschinellen Lernens" or corresponding knowledge
  • Mastery of a programming language (e.g. Python)
Topic: IT & Digitalisation
Format of course: (Vor-Ort-)Präsenz und Online
Level: Master
Course language: English
Study programme
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
Qualifikationsziele

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