Workload:
180 h
|
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 | English | |
| 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 2025 | |
| Assigned Study Areas | BIOINFM2510, INFM2510, INFM3110, INFM3410, MDZINFM2510, MEINFM3210 | |