Industrial Data Science 2 Summer 2023

Kick-off

The first meeting will take place on April, 14th from 10.15-11.45.

Moodle

All relevant course information can be found in the Moodle room.

Description

Industrial Data Science 2, or InDaS 2 for short, is an interdisciplinary course that builds on the master's course Industrial Data Science 1. In the summer semester, students from the faculties of Mechanical Engineering, Statistics and Computer Science work on real-world data science use cases from industry. The use cases come from diverse industries, such as electronics manufacturing, the automotive industry or the chemical sector.

In the course format, which is referred to as problem-based learning, students develop independent solutions to existing real-world problems. To do this, they use their knowledge from the previous course in the winter semester and acquire new skills for solving the use cases in a systematic manner. Just as diverse as the domain are the use cases, e.g. image recognition, signal processing, time series clustering or process prediction.

The course organizes small groups of about six to eight students, each of whom deals with one of four use cases. During the semester there are three presentation dates in which interim results of the work are presented. The groups act as advisory teams and present their work in a descriptive fashion. Among others, the four professors and the use case owners from the industrial use cases take part in these meetings.

There will also be an introductory session during which the four use cases will be presented. Students are then given the opportunity to indicate a priority. The assignment of the groups is done taking this prioritization into account. In the event of a tie, the decision will be made by drawing lots.

In addition to presenting their findings during the semester, students will prepare a written report of their analysis. The work on the report is done during the semester and by each student individually.