Machine Intelligence: Concepts and Applications- M.Sc/ P.hD





General Information



  • 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: 26.04.2019 – 10.05.2019 via Flexnow.
  • First-come, first-served!
  • Materials: Stud.IP.




Syllabus



Lectures
Block 1. from 9:00 to 17:00 on 26.04.2019 at ZHG006;

Block 2. from 9:00 to 12:00 on 10.05.2019 at VG 4.101;
from 13:00 to 17:00 on 10.05.2019 at VG 3.103;

Block 3. from 9:00 to 17:00 on 17.05.2019 at Theologicum - Theo -1.113;

Block 4. from 9:00 to 17:00 on 21.06.2019 at Theologicum - Theo -1.113;



Exam


  • Exam: 09.08.2019 (10:00 - 12:00, VG 3.103)




Learning objectives



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.

Contents:
• 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