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.