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M.Sc.|MBA|Micro Degree BDAI_logic-ai
Logic and Symbolic AI

This module is an introduction to symbolic AI. First the basics of logic systems is discussed, followed by the presentation of combinatorial algorithms for the solution of AI problems. Prolog is used as the implementation language. The students learn to prove assertions of predicate logic and implement simple proof systems in Prolog.

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Logic and Symbolic AI

About This Course

This module is an introduction to symbolic AI. First the basics of logic systems is discussed, followed by the presentation of combinatorial algorithms for the solution of AI problems. Prolog is used as the implementation language. The students learn to prove assertions of predicate logic and implement simple proof systems in Prolog.

Learning Objectives

  • Learn the basics of logic and proof systems.
  • Understand and apply combinatorial algorithms.
  • Develop skills in the programming of symbolic AI systems.
  • Practice teamwork around benchmark problems.
  • Be able to apply different proof methods to solve symbolic problems.

Study Programs

This course is mandatory for the following study programs.

  • M.Sc. Applied AI

This course is offered in odd quarters and can, therefore1, be selected as an elective in the following study programs:

  • M.Sc. Cybersecurity
  • M.Sc. Advanced Digital Reality
  • M.Sc. Digital Leadership
  • MBA Digital Technologies
  • MBA Digital Transformation

1: Generally all mandatory modules of a study program can be selected as an elective in all study programs in which they are not offered as a mandatory module. However, there are several rules that apply. First, at least half of the selected electives have to be taken from your study program. Second, all electives are only available in either odd or even quarters. Therefore, not all electives are available in all programs (given that you want to finish the program within the regular time frame and do not want to take that elective in parallel to your impact project.)

Micro Degree

  • This course is offered as a micro degree.
  • German UDS Micro Degrees are compatible with the European MOOC Consortiums Common Micro Credentials Framework.
  • Micro Degrees will be rewarded with an equivalent of 5 ECTS.
  • Micro Degrees are offered to non-regular students and require a fee of €900.

Requirements

Basic programming skills. Knowledge and skills as provided in the Prep courses.

General Information

  • Teaching Format: Knowledge Essential
  • Total Workload Master: 125h (40h/85h) / 5 ECTS
  • Total Workload MBA: 100h (40h/60h) / 4 ECTS
  • Total Workload Micro Degree: 125h (40h/85h) / Equivalent to 5 ECTS
  • Module coordinator: tbd
  • Examinations: Quizzes, presentation(s), essay(s)/paper(s), project report(s), written exam (tbd) - Details will be announced with course start.
  • Offered: Odd quarters

Course Staff

Dr. Felix Weitkämper

Dr. Felix Weitkämper

Felix has completed his undergraduate education in Mathematics with Philosophy at the LMU in Munich. Afterwards, he completed a doctorate in Mathematics with the Logic Group at the University of Oxford. After graduating from Oxford, he spent a year teaching 15-19 year olds at a technical college in the North of England as part of the Researchers in Schools initiative, which brought postgraduates from selective universities into schools in disadvantaged parts of England. In 2020, Felix moved into computer science and joined the programming languages and AI group at the LMU in Munich as a postdoctoral researcher. His research focus lies on interpretable, human-centered AI, and in particular on the combination of statistical learning and modelling with sophisticated logical reasoning. Within this field, his work spans from mathematical foundations to systems and applications in the life sciences. He will be part of the German UDS family from October 2024 as a full-time senior researcher, doing his part for the new generation of AI specialists and deciders to be grounded in the whole breadth of AI research and technique.

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