Communication Technology 2
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Communication Technologies 2 - Machine Learning: Applications and Algorithms
Creditability:
- Computer Science Master's program: 4 SWS
- Electrical Engineering Master's program: 4 SWS
- Master Program Electrical Communication Engineering: 4 SWS (lecture + lab course)(only for students starting before 2024)
Lectures:
Thursdays 11:00 to 12:30
Lecture type:
Programming part and presentations
Language:
By arrangement
Target audience:
- Computer science - Computer engineering
- Electrical Engineering - Communications Engineering
- Master Program Electrical Communication Engineering(only for students starting before 2024)
Prerequisites:
- Basic knowledge of software development
Content:
The content of the lecture includes the following topics:
- Advanced and current topics in the fields of machine learning and data mining
- Application of machine learning algorithms, e.g.
- Activity Recognition II: Evaluation metrics / Instance based vs. pattern based evaluation
- Time Series Segmentation Algorithms
- Alignment Algorithms for Context Prediction
- WiFi Fingerprinting
- Dead Reckoning / Multi Sensor Data Fusion
- Attention Management Systems
- Gaussian Mixture Models
- Home Automation
- Introduction to writing scientific papers
- Writing scientific papers and presentations as well as programming
Practical course:
The laboratory practical Communication Technologies 2 is integrated into the course.
Registration
Registration will take place in eCampus from September.
First event date
Thursday, 16.10.2025, 11:00 a.m., lecture hall -1605
Place and time
Thursdays:
WA 73, lecture hall -1605, 11:00 - 12:30, until 14:00 if required
Moodle
Anyone who has been allocated a place will be entered in the Moodle course by us, there is no self-enrollment.