Wintersemester 2022 / 2023

Module Aims

The course “Machine Learning and Data Mining (MLDM)” covers the fundamentals and basics of machine learning and data mining. The course provides an overview of a variety of MLDM topics and related areas such as optimization and deep learning.

Learning Methods

This year, we employ blended learning as an approach to learning and teaching. This means that we will grant access to pre-recorded lecture material via OLAT, as well as provide opportunities for interaction with our tutors and student peers during the tutorial sessions. We will release new learning materials each week.

Assessment

Students are expected to independently engage with the online lecture materials as well as complete weekly group assignments. The assignments will be disussed during weekly tutorial sessions. In order to complete the module (6 ECTS), students first have to pass a threshold‚ score in these weekly exercises, which then qualifies them to sit the final exam. The threshold to pass the exam is 50%.

Enrolment

The module is available to students enrolled in various programmes offered by Fachbereich 4. For further details on eligibility and on how to enrol, we refer to KLIPS. OLAT will be used for sharing learning materials and for further module-related communication.

Lehrende