back to search

Projektpraktikum Multimedia

EI05381Specialization in Technology6 ECTSGerman/Englishwinter semesterDepartment Computer Engineering
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You develop multimedia applications in small teams with a machine-learning backend and a web frontend. You acquire practical knowledge in machine learning, Python and web programming and will be able to implement and present a cross-platform web application for multimedia processing.

What you will be able to do

  • Understand the basics of machine learning for multimedia processing
  • Master concepts of responsive web design
  • Select and deploy suitable neural networks for a given problem
  • Develop cross-platform web applications for multimedia processing
  • Analyze and evaluate results of AI models
  • Plan, implement and defend a project in a presentation

What the module consists of

  • Laborsitzungenweekly practical units to develop fundamental knowledge in ML, Python and web programming
  • Praktisches Projekt (Gruppenarbeit)Main project: topic finding, dataset preparation, training of networks, implementation of a web application, project planning and presentation
  • PraktikumsaufgabenPreparatory implementations (e.g., Python, dataset preparation, fine-tuning) to prepare for the project

Teaching method

  • praktische Laborarbeitenhanced knowledge acquisition through practical implementation and supervision
  • wöchentliche Laborsitzungen mit Frontaleinheitencombination of introduction and intensive supervision during the session

Dates

Lab courseProjektpraktikum Multimedia

  • Wed13:00–17:000943, Praktikum (0509.EG.943)
    15× · 14.10.–03.02.
    • 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.
    • 03.02.

From the current semester, not binding.

Module ratings

No ratings for this module yet.

Rate this module

Only fill in the categories you can judge – for each one, either stars and text together or nothing at all.

Lecture
Tutorial
Exam

Reviews are automatically checked before they are published.

Official page in TUMonline · Details are not binding.