IND310 Driftsoptimalisering

The main course is in two parts. Part one covers operational optimization using data science. Optimization deals with, among other things, context understanding, method overview, process analysis, data information, models and simulation.

Part two is about master's preparation, where methodology and master's writing are taught, and a preliminary project for the master's thesis must be submitted.

Students should have a good understanding of methods, as well as an understanding of how to write a master's thesis. When the course is completed, students should be able to manage operations, analyze, and optimize processes. Emphasis will be placed on providing students with knowledge of specific tools. There is a clear goal of the students gaining practical insight into the topics covered in the course.

After completing the course

Our focus is on approaches to digital decision support. IND310 will look at different contexts from different sectors from the Industry Classification Benchmark (ICB): Health, Financial, Energy, Aquaculture, and others. To make good decisions when working with data, we will first learn approaches to digital operations management through the CRISP-DM methodology.