back to search

Fundamentals of Artificial Intelligence

IN2406Master's Modules6 ECTSEnglishwinter semesterDepartment Computer Engineering
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You learn the foundations of artificial intelligence: from search procedures and constraint-satisfaction to logic and probabilistic models to decision making, learning and an introduction to robotics. In the end you will be able to design simple AI systems and apply basic methods from search, logic, probability and decision theory.

What you will be able to do

  • Analyze AI problems and assess their difficulty
  • Know the basic concepts of intelligent agents and task environments
  • Formalize search problems and apply search procedures
  • Differentiate, apply and evaluate constraint-satisfaction problems
  • Critically assess the advantages and disadvantages of logical approaches
  • Describe problems with propositional and predicate logic formally
  • Apply automatic reasoning in propositional and predicate logic
  • Understand the advantages and disadvantages of probabilistic methods compared to logic-based methods
  • Apply and assess methods of probabilistic inference (Bayesian networks, HMMs)
  • Formalize and compute rational decisions
  • Know the basics of machine learning
  • Know fundamental areas and concepts of robotics

What the module consists of

  • VorlesungDelivery of content through slides, blackboard and/or electronic writing tablet
  • ÜbungenApplication of the lecture content to practical examples; problem solving recommended before attending

Teaching method

  • Vorlesung mit Folien und Tafel/elektronischem Schreibpadfor systematic presentation of the content
  • Übungsgruppen mit Aufgabenfor deepening and practical application of the lecture material
  • Interaktive Fragen/Online-Pollsto encourage participation and assess understanding
  • Optional programming assignmentspractical incentives; completion of certain requirements yields a bonus on the exam grade

Dates

Lecture with exerciseFundamentals of Artificial Intelligence (IN2406)3 groups to choose from

  • AThu16:00–18:00MW 0001, Hörsaal (5510.EG.001)
    14× · 15.10.–04.02.
    • 15.10.
    • 22.10.
    • 29.10.
    • 05.11.
    • 12.11.
    • 19.11.
    • 26.11.
    • 10.12.
    • 17.12.
    • 07.01.
    • 14.01.
    • 21.01.
    • 28.01.
    • 04.02.
  • BThu18:00–19:00MW 0001, Hörsaal (5510.EG.001)
    14× · 15.10.–04.02.
    • 15.10.
    • 22.10.
    • 29.10.
    • 05.11.
    • 12.11.
    • 19.11.
    • 26.11.
    • 10.12.
    • 17.12.
    • 07.01.
    • 14.01.
    • 21.01.
    • 28.01.
    • 04.02.
  • CFri13:00–14:30MW 2001 Rudolf-Diesel-Hörsaal (5510.02.001)
    14× · 16.10.–05.02.
    • 16.10.
    • 23.10.
    • 30.10.
    • 06.11.
    • 13.11.
    • 20.11.
    • 27.11.
    • 04.12.
    • 11.12.
    • 18.12.
    • 08.01.
    • 15.01.
    • 22.01.
    • 05.02.

From the current semester, not binding. You attend one of several groups; the timetable automatically suggests the one with the fewest clashes.

Show TUMonline data
Sprache
Englisch
Turnus
Wintersemester
Modulniveau
Bachelor/Master
Moduldauer
Einsemestrig
Gesamtstunden
180
Präsenzstunden
75
Eigenstudiumstunden
105
Organisationsname
Department Computer Engineering

Courses

  • Fundamentals of Artificial Intelligence
  • Fundamentals of Artificial Intelligence

Official page in TUMonline · Details are not binding.