Lecture: Foundations of Machine Learning and Data Mining

Lecturers: Ralf Möller


Basic knowledge in Computer Science, Discrete Mathematics, Linear Algebra, Mathematical Analysis, Probability Theory, Statistics
Knowledge in Intelligent Autonomous Agents would be a plus

Educational Objectives:

After the course Bachelor students have expertise about basic machine learning and data mining techniques as well as analytical skills to match pros and cons of techniques to requirements in applications. With this course students develop prerequisite capabilities for a more in-depth Master-level course on Cognitive Robotics or Probabilistic Models of Human and Machine Intelligence.

Content :


Slides are taken from courses by Ethem Alpaydin, Stuart Russell, Hwee Tou Ng, Y. Hou, Eamonn Keogh, Xiaoli Fern, Carla P. Gomes, Nathalie Japkowicz et al.


Previous exams

Ralf Möller