Introduction to Artificial Intelligence in Finance (WiSe 2025/26)

Veranstaltungszeitplan

Hinweis

This course introduces students to the fundamentals of artificial intelligence, machine learning, and the data-science lifecycle, with a strong focus on real-world applications in financial research and practice. Through a mix of theory, hands-on coding, and case studies, students will learn how AI is used in areas such as credit scoring, algorithmic trading, and fraud detection. Covered topics include data preprocessing, supervised and unsupervised learning, model evaluation, and reinforcement learning. The course puts a lot of focus on practical exercises using financial datasets and Python. Students will have to complete a take-home assignment as well as pass an exam to successfully pass this class.

Disclaimer:

This course is designed for students with basic programming experience (including knowledge of variables, loops, if-else-statements, and functions) in any programming language (not necessarily in Python) and a foundational understanding of regression analysis. Please be advised that pre-registration on the FCM homepage is essential as the course is limited to 15 students. Registration is possible until October 19, 2025, on the homepage of the Finance Center: https://www.wiwi.uni-muenster.de/fcm/en/introduction-artificial-intelligence-finance#overlay-context=de/studium/lehrveranstaltungen/450057

Beschreibung

Dozenten

• Prof. Dr. Thomas Langer (verantwortlich)
• Dr. Lennart Stitz (verantwortlich)