Machine Intelligence: Concepts and Applications- M.Sc/ P.hD
- Module: Machine Intelligence: Concepts and Applications
- Module number lecture: M.WIWI-WIN.0026
- UniVZ: 801478
- Cycle: Summer Semester
- Credits: 6 ECTS
- Courses of study: Master WI, Master Ufü, Master Economics, Master Applied Computer Science, Offer to all M.Sc/ P.hD
- Type of teaching and learning: Lecture (8 Block Courses)
- Examination: Written Examination
- Language: English
- Lecturers: Prof. Mohit Kumar (University of Rostock)
- Contact: Yachao Yuan
Course specific information
- Registration process: Registration via FlexNow is mandatory. Registration Period: 24.04.2020 - 08.05.2020 via Flexnow.
- First-come, first-served!
- Materials: Stud.IP.
Block 1,2. from 9:00 to 17:00 on 24.04.2020 -
Block 3,4. from 9:00 to 17:00 on 08.05.2020 -
Block 5,6. from 9:00 to 15:00 on 15.05.2020 –
from 15:00 to 17:00 on 15.05.2020 –
Block 7,8. from 9:00 to 17:00 on 19.06.2020 -
All lectures will be taught online over Microsoft Teams on the above dates. More detailed instructions are given in StudIP. For better learning experience, enrollment in StudIP is highly recommended. Please feel free to contact me if you have any question about our course.
- Exam: 03.07.2020 (10:00 - 12:00,
The course would introduce the context of computational algorithms in broader areas of Machine Learning, Data Mining, Signal Processing, and Image Processing. The course would remain focused on the study of machine learning and fuzzy computing algorithms with practical applications to Computer Vision, eHealth & mHealth, and Water Distribution System. At the end of the course, the participants should be capable of applying intelligent computing algorithms to address the challenging issue of “uncertainties” in the real-world problems related to data modeling and analysis.
• Artificial Intelligence and Machine Learning
• Stochastic Approach to Modeling
• Fuzzy Approach to Modeling
• Image Matching Applications
• Biomedical Signal Processing Applications in eHealth and mHealth
• Big Data Analysis Applications in Water Distribution System Modeling