Workload:
180 h
|
Module Number INF3155 |
Module Title Artificial 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 | Irregular | |
| Language of instruction | German and English | |
| Type of Exam | Internship performance including lecture and essay |
|
| Lecture type(s) | Practical Course | |
| Content | Students become familiar with neural network simulators (JavaNNS, Weka, Matlab) and various network models and training methods in teams of about 3 students, and solve a real pattern recognition problem in teams of 2-3 students in the second half of the lab. |
|
| Objectives | Students learn to apply the models from the lecture to a larger real-world problem. Students will also learn problem analysis, teamwork, time management, documentation, and presentation techniques. |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%) |
|
| Prerequisite for participation | INF3154 Introduction to Neural Networks | |
| Lecturer / Other | Zell | |
| Literature | Wird in der Vorbesprechung ausgeteilt. |
|
| Last offered | unknown | |
| Planned for | currently not planned | |
| Assigned Study Areas | BIOINFM2510, INFM2510, INFM3110, MDZINFM2510, MEINFM3210 | |