14015 - Introduction to Mathematical Methods in Artificial Intelligence Modulübersicht

Module Number: 14015
Module Title:Introduction to Mathematical Methods in Artificial Intelligence
  Einführung in mathematische Methoden der künstlichen Intelligenz
Department: Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
Responsible Staff Member:
  • Prof. Dr. rer. nat. habil. Breuß, Michael
Language of Teaching / Examination:English
Duration:1 semester
Frequency of Offer: On special announcement
Credits: 6
Learning Outcome:After successfully completing the module, students will be acquainted with basic principles and main techniques of mathematical methods that are useful in artificial intelligence and machine learning. They understand the inner workings of the techniques. They are able to apply the presented methods.
Contents:In the lectures the theory and methods are presented. The knowledge about the material is deepened in self-organised studies and practized in the tutorial at hand of homework problems.

Major topics are:
  • important concepts in linear algebra, e.g. matrix factorization
  • analytic geometry, e.g. projection mappings
  • linear regression
  • matrix factorization, e.g. Cholesky decomposition
  • vector calculus and its use in optimization, e.g. in gradient descent
  • probability and distributions, e.g. Bayes’ theorem
  • dimensionality reduction, e.g. by principal component analysis
  • selected applications in artificial intelligence
Recommended Prerequisites:Knowledge of calculus and linear algebra, e.g. knowledge of the content of the modules
  • 11113 Mathematik IT-2 (Lineare Algebra)
  • 11213 Mathematik IT-3 (Analysis)
Mandatory Prerequisites:None
Forms of Teaching and Proportion:
  • Lecture / 2 Hours per Week per Semester
  • Exercise / 2 Hours per Week per Semester
  • Self organised studies / 120 Hours
Teaching Materials and Literature:
  • „Mathematics for Machine Learning“, Deisenroth, Faisal, Ong, Cambridge University Press, (2020)
Module Examination:Final Module Examination (MAP)
Assessment Mode for Module Examination:
  • Written Examination, 90 minutes
Evaluation of Module Examination:Performance Verification – graded
Limited Number of Participants:None
Part of the Study Programme:
  • Master (research-oriented) / Artificial Intelligence / PO 2022
  • Abschluss im Ausland / Informatik / keine PO
  • Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex  „Advanced Methods“
Module Components:
  • Lecture: Introduction to Mathematical Methods in Artificial Intelligence
  • Accompanying exercise
  • Related examination
Components to be offered in the Current Semester: