Content
1 Introduction
2 Data acquisition etc.
3 Timeseries analysis
4 Sentiment analysis
5 Risk management
6 Fraud detection
7 Portfolio optimization
Learning objectives
This material is an introduction to using artificial intelligence (AI) in the frame of financing applications. First we cover the basic ideas of machine learning models. Then selected use cases from financing are discussed with practical examples using Python programming language. The reader is strongly advised not only to run sample code but tweak code parameters to see their full effect and meaning.
The reader is assumed to have a working knowledge of Python. Basics of AI and machine learning are mostly assumed, also, but those follow along the lines of our previous course. Elementary understanding of financial concepts is also helpful but we will explain them as we go.
Teaching methods
Course is 100% online (self-study) course which can be done in own pace.
Course includes 7 Chapters which have to be done in order.
Learning material and recommended literature
Can be find via workspace.
Evaluation criteria
Pass/Fail
Grading criteria's can be find via workspace or you can ask them via viopesupport@metropolia.fi
Opettaja/Yhteyshenkilö
Janne Salonen