Module


General information
Deep Learning
Deep Learning
MADS-DL
DeepLearnC-01-MA-M
Prof. Dr. Doerfel, Stephan (stephan.doerfel@haw-kiel.de)
Prof. Dr. Doerfel, Stephan (stephan.doerfel@haw-kiel.de)
Wintersemester 2025/26
1 Semester
In der Regel jedes Semester
Englisch
Curricular relevance (according to examination regulations)
Study Subject Study Specialization Study Focus Module type Semester
M.Sc. - DS - Data Science Pflichtmodul

Qualification outcome
Areas of Competence: Knowledge and Understanding; Use, application and generation of knowledge; Communication and cooperation; Scientific self-understanding / professionalism.
Students know
- the fundamentals of neural networks.
- the most commonly used concepts of neural network based learning.
- standard tools for deep learning.
Students are able to
- setup deep learning experiments.
- apply deep learning algorithms in practice.
- use deep learning algorithms for real-world problems.
Students are able to
- critically assess and compare the results of deep learning algorithms.
- give and accept professional feedback to different topics of deep learning.
Students are able to
- work professionally in the field of deep learning.
- select relevant scientific literature about deep learning.
Content information
Introduction to
- Artificial Intelligence
- Neural Networks
- Deep Learning
- Computer Vision

Concepts
- Perceptrons
- Multilayer Forward Networks
- Neural Networks for Classification and Regression
- Computer Vision and Convolutional Layers
- Time Series and Recurrent Neural Networks
- Transfer Learning

Applications
- Classification
- Regression
- Computer Vision
- Time Series Forecasting
- Lecture Slides
- Additional literature
- Stevens, Antiga and Viehmann: Deep Learning with PyTorch. Manning (2020).
Available online:
https://www.manning.com/books/deep-learning-with-pytorch
Teaching formats of the courses
Teaching format SWS
Lehrvortrag + Übung 4
Workload
4 SWS
5,0 Credits
48 Hours
102 Hours
Module Examination
No additional requirements
Method of Examination Duration Weighting wird angerechnet gem. § 11 Absatz 2 PVO Graded Remark
Portfolioprüfung 100 %
Miscellaneous
Basic Knowledge of Python
Basic Knowledge of Machine Learning (particularly, the module MADS-ML)