Study Guide

Objective

The students are introduced to artificial intelligence (AI) and machine learning (MI) concepts and applications in the field of Industrial Management and Engineering. The students will gain insights into the analysis process that starts with problem identification and data collection, continues with choice of appropriate tools and ends with an evaluation of the results. During the course the student is given the opportunity to apply the lessons learnt to a problem from their own day-to-day work environment.

Content

The course seeks to answer the following questions:
- What is AI and ML?
- Where and how are AI and ML learning used today?
- What added value can AI and ML bring to Industrial
Management and Engineering?
- How are different models created for AI and ML?
- What methods and tools are used within AI and ML?
- How are the results of AI and ML evaluated?

Materials

- Steven Finlay 2017. Artificial Intelligence and Machine Learning for Business.
- Ajay Agrawal, Joshua Gans and Avi Goldfarb 2018. Prediction Machines.
- Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani 2017. An Introduction to Statistical Learning: with Applications in R.
- Journal articles suggested by the examiner.
- Meriluoto, Antti 2018. Tekoäly, matkaopas johtajalle.
- Tegmark, Max 2017. Att vara människa i den artificiella
intelligensens tid.

Evaluation scale

H-5

Qualifications

See Study Handbook 12-2018, page 17