To content
Department of Statistics

Industrial Data Science 1 Winter 23/24

Course Structure

Lecturers

Prof. Dr. Jochen Deuse

Prof. Dr. Erich Schubert

Prof. Dr. Markus Pauly

Prof. Dr. Jens Teubner

Dates

Lecture:  Friday 08:15-09:45 am at EF50, HS 1
Exercises: Friday 10:15-11:45 am at SRG1, H.001

Language and Format

  • The course will be held in English.
  • Both lecture and exercises will be taught offline.
  • Attendance of the exercise is optional, but strongly recommended especially with regard to required competencies in project management and programming in Indas 2.

Suitable modules

MS 6,7; MD Applications (5 ECTS points)

Registration

Registration is via Moodle.

Course: Industrial Data Science 1 WS 23/24, LSF, 042537

Link: will be added soon

Course outline

The course covers  the basics of data mining and data management as well as their industrial applications.  Specifically, the lectures will embrace the following topics, among others:

  •     Data and data analysis in industrial environments
  •     Data Management
  •     Univariate statistics, correlation and regression, feature selection
  •     Decision trees and random Forests
  •     Cluster analysis and topic modeling
  •     Model selection
  •     SVMs and neuronal networks

Prerequisites

Basic knowledge in math and programming

Follow-up course

In the summer term 2024, a course Industrial Data Science 2 will be offered, in which the learned, theoretical material can be practically applied to real industrial use cases. This course can be credited for master of data science students as MD Applications (5 ECTS)

Further information about the course concept can be found here.

Contact