Introduction to Machine Learning 

The objective of the course Introduction to Machine Learning is to provide an introduction to (supervised) machine learning tools suitable for classification problems in finance. Students will learn the basic underlying mathematical concepts of several classification algorithms with the main focus being on practical applications of the discussed algorithms using Python as a programming language.

Prerequisites

Successful completion of modules ’Statistics (22AOEC10)’ and ’Introductory Econometrics (22BO0002)’. Programming is becoming an integral part of future finance. In that sense, students with no prior knowledge in Python programming are highly encouraged to apply for this course. However, due to the limited time available, it is understood as prerequisite that students have learned the basics of Python programming prior to the first class session - up to the level of chapters 1-3 of Jake Vanderplas’ book ’Python Data Science Handbook’ (available here: https://jakevdp.github.io/PythonDataScienceHandbook/). A hands-on starting point is to work through DataCamp’s open course ’Intro to Data Science’ at https://www.datacamp.com/courses/intro-to-python-for-data-science. Prior knowledge in programming is not required but students should be aware of the efforts it takes to learn a programming language.

Registration

The number of participants is limited. Your application is to be handed in on OLAT before 12.12.2022. If you are accepted, do not forget to also register as usual in the module booking system. Your application is to be handed in on OLAT.

In a nutshell

• 3 ECTS Credits
• for Bachelor students
• in English
• application in the fall term, takes place in the spring term
• limited number of participants

Please note the information in the VVZ - if in doubt, these apply.