From linear regression to LLM agents.
Open lecture materials for two graduate courses taught by Dr. Zonghao Yang: FA590 Statistical Learning in Finance and FA690 Machine Learning in Finance.
Two courses, one arc
Statistical Learning builds the foundation; Machine Learning carries it into deep learning and generative AI. Together they trace the full path from classical models to the systems now reshaping the finance industry.
Statistical Learning in Finance
The foundation: regression, classification, model selection, support vector machines, tree ensembles, neural networks, and unsupervised learning, applied to asset pricing, portfolio optimization, and credit risk.
View course & slides → FA690Machine Learning in Finance
The deep end: CNNs, RNNs and LSTMs, attention and the Transformer, financial NLP, and large language models, through to retrieval-augmented generation and LLM agents for decision-making in finance.
View course & slides →Which topics matter for your goal?
Tell the assistant where you want your career to go. It maps your goal to the specific weeks of FA590 and FA690 that build those skills.
Answers are AI-generated from the published course schedules and may be imperfect. For academic advising, contact the instructor.
What students say
The best class since I started studying at Stevens.
Despite having no prior experience in machine learning or coding, I thoroughly enjoyed the course. Professor Yang made the material clear and answered all my questions, in class and in office hours. His patience and dedication made a challenging subject approachable. Thank you, Professor Yang!
Professor Yang went above and beyond for his students, responded quickly to emails, and has a strong command of the subject.
I really liked how the course combined statistical learning techniques with real financial applications. The assignments and final project showed me how machine learning models apply to real-world financial datasets.
I liked learning the mechanics of building neural networks and transformer models. Now I understand what they can do, and they don't seem like black boxes anymore.
I really liked the visuals and examples the professor used. He was very organized and went at a good pace, not too fast and not too slow. Great class.
Great course. I learned a lot about deep learning and language models, and it covers a lot of state-of-the-art research in the area.
The professor is amazing. He is really knowledgeable and makes sure we understand everything.
The professor is really good and very kind. If we have any doubt, he explains it from scratch.
Where these courses live
Both courses are taught within two graduate programs at the Stevens School of Business.
Financial Technology & Analytics
Data-driven finance: machine learning, data science, and financial technology at the intersection of business and computing.
Program details ↗ Master'sFinancial Engineering
Quantitative and computational finance: stochastic modeling, derivatives, and risk, for careers in quantitative research and trading.
Program details ↗
Dr. Zonghao Yang
Tenure-track Assistant Professor of FinTech at the School of Business, Stevens Institute of Technology. Dr. Yang holds a PhD in Data Science from City University of Hong Kong, and his research focuses on financial technology and applied machine learning.
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