Deep Learning and GANs
Deep Learning och GANs

FRT220F, 6 credits

Valid from: Spring 2019
Decided by: Professor Thomas Johansson
Date of establishment: 2019-11-25

General Information

Division: Automatic Control
Course type: Third-cycle course
Teaching language: English

Aim

Learn about deep learning and GANs.

Goals

Knowledge and Understanding

For a passing grade the doctoral student must

• Know the deep learning foundation.
• Understand deep learning training and its challenges.
• Understand basics or more advanced methods such as GANs.

Competences and Skills

For a passing grade the doctoral student must Be able to implement different machine learning methods in different programming languages.

Judgement and Approach

For a passing grade the doctoral student must Know which problems different machine learning methods can and should be used.

Course Contents

Three modules: - Deep learning basic - Deep learning training - Advanced deep learning

Course Literature

Slides and videos.

Instruction Details

Types of instruction: Lectures, seminars, exercises, project. Three two day workshops covering: - Deep learning basic - Deep learning training - Advanced deep learning

Examination Details

Examination format: Written assignments
Grading scale: Failed, pass
Examiner:

Admission Details

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page: https://wasp-sweden.org/deep-learning-and-gans-6-credits/