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Artificial Intelligence for Supply Chain Management

MGT001500Specialization in Management6 ECTSEnglishwinter semesterLehrstuhl für Logistik und Supply Chain Management (Prof. Minner)
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You learn the basics and methods of artificial intelligence with a focus on applications in supply chain management and logistics. In the end you will be able to assess AI procedures for tasks such as network design, forecasting, inventory management, procurement and agent coordination and apply them in simple projects.

What you will be able to do

  • Overview of AI in Supply Chain Management
  • Application of Machine Learning and generative AI methods
  • Use of agent-based AI and Human-AI interaction
  • Development and implementation of AI-based solutions for SCM tasks
  • Analysis of strengths and weaknesses of the methods

What the module consists of

  • VorlesungDelivery of theoretical concepts and fundamentals
  • Übungen / AssignmentsPractice with concrete tools and methods through weekly tasks
  • ProjektApplication of the learned methods to a practical problem

Teaching method

  • VorlesungExplanation of concepts and methods
  • ÜbungsaufgabenPractical application and deepening through weekly tasks
  • ProjektarbeitImplementation of an AI solution in a realistic scenario

Dates

SeminarArtificial Intelligence for Supply Chain Management (MGT001500, englisch) (Limited places)2 groups to choose from

  • ATue15:00–16:301100, Hörsaal ohne exp. Bühne (0501.01.100)
    14× · 13.10.–26.01.
    • 13.10.
    • 20.10.
    • 27.10.
    • 03.11.
    • 10.11.
    • 17.11.
    • 24.11.
    • 01.12.
    • 08.12.
    • 15.12.
    • 22.12.
    • 12.01.
    • 19.01.
    • 26.01.
  • BWed11:30–13:001180, Hörsaal ohne exp. Bühne (0501.01.180)
    14× · 14.10.–27.01.
    • 14.10.
    • 21.10.
    • 28.10.
    • 04.11.
    • 11.11.
    • 18.11.
    • 25.11.
    • 02.12.
    • 09.12.
    • 16.12.
    • 23.12.
    • 13.01.
    • 20.01.
    • 27.01.

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

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Official page in TUMonline · Details are not binding.