Module Number

INF3154
Module Title

Introduction to Neural Networks
Type of Module

Elective Compulsory
ECTS 6
Work load
- Contact time
- Self study
Workload:
180 h
Class time:
60 h / 4 SWS
Self study:
120 h
Duration 1 Semester
Frequency In the summer semester
Language of instruction German
Type of Exam

Written Test

Lecture type(s) Lecture, Tutorial
Content

In the lecture, after a short introduction to the biological basics, the most important algorithms of artificial neural networks and their theory are presented. In the exercise, the theoretical knowledge is deepened by solving practical tasks with neural network simulators.

Objectives

The aim of this module is to provide basic knowledge about neural networks. Students learn about the most important network models and their properties. They learn to use them to solve pattern recognition problems (classification, regression). In some cases they also program network models themselves or use modern simulators (JavaNNS, JMatlab).

Allocation of credits / grading
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%)
Prerequisite for participation There are no specific prerequisites.
Lecturer / Other Zell
Literature

Skriptum zur Vorlesung, und Lehrbuch A. Zell: Simulation neuronaler Netze, Oldenbourg-Verlag

Last offered Sommersemester 2022
Planned for Sommersemester 2024
Assigned Study Areas BIOINFM2510, INFM2510, INFM3110, INFM3410, MDZINFM2510, MEINFM3210