FA690

Machine Learning in Finance

An advanced course on deep learning and generative AI, and how they are used in the finance industry.

Building on the foundations of statistical learning, Machine Learning covers the architectures behind modern AI: convolutional neural networks, recurrent networks and LSTMs, and the attention mechanism at the heart of the Transformer, with dedicated sessions on their applications in financial prediction and natural language processing.

The final module turns to generative AI. Students study how large language models work and how to use them effectively (prompting, retrieval-augmented generation, and fine-tuning) before examining LLM agents and agentic workflows and their growing role in financial decision-making.

Schedule

Course schedule & slides

Lecture slides for each week are linked below as PDFs.

01Foundations

#	Topic	Slides
1	Introduction to Machine Learning
2	Review of Statistical Learning
3	Neural Network Basics

02Computer Vision

#	Topic	Slides
4	Convolutional Neural Networks
5	CNN Applications in Finance

03Natural Language Processing

#	Topic	Slides
6	NLP and Word Embedding
7	Recurrent Neural Networks and Long Short-Term Memory (LSTM)
8	Attention Mechanism and Transformer
9	NLP Applications in Finance

04Generative AI

#	Topic	Slides
10	Introduction to Generative AI and Large Language Models
11	Use of LLMs: Prompting, Retrieval-Augmented Generation, and Fine-Tuning
12	LLM Agents and Agentic Workflows

Reading

Textbooks

Deep Learning

Ian Goodfellow, Yoshua Bengio, and Aaron Courville

MIT Press, 2016

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Dive into Deep Learning

Aston Zhang, Zach C. Lipton, Mu Li, and Alex J. Smola

Cambridge University Press, 2023

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