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Machine Learning for Electronic Design Automation and Manufacturing

CIT433031Elective Modules Informatics5 ECTSEnglishWintersemester/SommersemesterDepartment Computer Engineering
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You will learn how machine-learning methods can support and improve the development, design, testing, and manufacturing of chips. The module combines theoretical fundamentals with current procedures and hands-on exercises, so you can apply machine-learning approaches to concrete design automation and manufacturing tasks.

What you will be able to do

  • Understand how ML is used in development, design, test, and manufacturing of chips
  • Recognize which design and manufacturing problems can be addressed in a data-driven way
  • Knowledge of requirements and best practices for ML adoption in industrial chip workflows
  • Familiarity with relevant data structures and state-of-the-art tools
  • Practical implementation and adaptation of ML algorithms for EDA- and manufacturing tasks

What the module consists of

  • VorlesungDelivery of the main concepts via slides and whiteboard sketches
  • Hands-on Sessions / ÜbungenDeepening through practical implementation and application of the algorithms

Teaching method

  • Presentations (Lectures)Introduction and explanation of core concepts
  • Hands-on exercisesPractice-oriented deepening and assessment of the feasibility of algorithms

Dates

Lecture with exerciseMachine Learning for Electronic Design Automation and Manufacturing

  • Fri13:00–16:00Online: Videokonferenz
    15× · 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.
    • 29.01.
    • 05.02.

From the current semester, not binding.

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Lecture
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Exam

Official page in TUMonline · Details are not binding.