RSM338: Winter 2026 archive

Archived lecture slides, notes, and assignments from Winter 2026 (20261), Applications of Machine Learning in Finance.
NoteArchived course · 20261

These are the materials for Winter 2026, preserved for reference. The current course homepage is being prepared for Winter 2027 · 20271; details are TBD. Browse all course archives.

Course Information

Instructor: Kevin Mott
Term: Winter 2026
Institution: Rotman School of Management

Lecture Materials

Lecture Topic Slides (Browser) Slides (PDF) Notes (Browser) Notes (PDF)
1 Math Bootcamp HTML PDF HTML PDF
Linear Algebra for Quantitative Finance – – HTML PDF
2 Financial Data HTML PDF HTML PDF
3 Introduction to Machine Learning HTML PDF HTML PDF
4 Clustering HTML PDF HTML PDF
5 Regression HTML PDF HTML PDF
6 ML & Portfolio Theory HTML PDF HTML PDF
7 Classification HTML PDF HTML PDF
8 Ensemble Methods HTML PDF HTML PDF
9 Neural Networks & Deep Learning HTML PDF HTML PDF
10 Textual Data HTML PDF HTML PDF

Assignments

For data, please see the relevant Quercus page.

Assignment Topic
1 Stock Returns
2 Clustering
3 Regression
4 MAXSER
5 Classification & Ensemble Methods
6 Neural Networks

Teaching Materials License

© 2026 Kevin Mott. Except where otherwise noted, only Kevin Mott’s original public RSM338 teaching materials, including archived offerings, are licensed under the Creative Commons Attribution–NonCommercial 4.0 International License (CC BY-NC 4.0), consistent with the teaching materials license on his main website. This license does not apply to other content on this website.

You may share and adapt those materials for noncommercial purposes, provided that you credit Kevin Mott, link to the original material and the license, and indicate whether changes were made. Third-party content, datasets, software, and institutional names, logos, and trademarks are excluded unless separately identified; their existing notices and licenses continue to apply. See the full legal code. For commercial permission, contact Kevin Mott through his faculty profile.