Schedule and rules

Rules

• Instructor. Ashleyn Castelino.

• Credit. You need to attend 3 sessions to get credit for the workshop.

• Why come to all 9. Three sessions earn the credit, but the chapters build on each other. Attending all of them gives you a strong base in each part.

• The goal. By the end you should be a strong quantitative analyst with working knowledge of agents, machine learning and finance.

• What you need. The most important skill in this course is curiosity. You need no technical background coming in, only the willingness to learn and to ask a lot of questions.

• If this pathway is not for you. If the course does not interest you, reach out to Prof. Ashish, who can recommend a project or assignment you can do for extra credit instead.

• Questions. Email Ashleyn at ashleyn4@illinois.edu.

Schedule

Session	Date	Time	Room	Part	Chapters
0	On your own time, before the workshop	Self-paced	No room	0 · Foundations for AI	0. How Large Language Models Work
1 ✓ Done	Fri, Sep 18, 2026	1:00–3:00 pm	3039 BIF	I · Agents	1. Introduction to AI Agents
2 ✓ Done	Fri, Sep 25, 2026	1:30–3:30 pm	3007 BIF	I · Agents	2. Prompt and Context Engineering
3 ✓ Done	Fri, Oct 2, 2026	1:30–3:30 pm	2043 BIF	I · Agents	3. Memory Retrieval and RAG
F	On your own time, before session 4	Self-paced	No room	Foundations for ML	Foundations for ML
4	Fri, Oct 16, 2026	1:30–3:30 pm	3007 BIF	II · Machine learning	4. ML Foundations I
5	Fri, Oct 23, 2026	1:30–3:30 pm	3007 BIF	II · Machine learning	5. ML Foundations II
6	Fri, Oct 30, 2026	1:30–3:30 pm	3007 BIF	III · Systems and decisions	6. Agent Systems
7	Fri, Nov 6, 2026	1:30–3:30 pm	3007 BIF	III · Systems and decisions	7. When to Use ML, Agents, or Neither
8	Fri, Nov 13, 2026	1:30–3:30 pm	3007 BIF	IV · Finance	8. Financial Markets and AI as an Investment Theme
9	Fri, Dec 4, 2026	1:30–3:30 pm	3007 BIF	IV · Finance	9. AI for Financial and Investment Research

Sessions 1, 2 and 3 are done; their lecture recordings are on the chapter pages. Session 4 is next (Fri, Oct 16).

Session 0, How Large Language Models Work, is self-paced: go through it on your own time before the workshop. It has no meeting, and you can start it now even if you have already attended a session. Before the next module (Part II, machine learning), work through Foundations for ML the same way: prices and returns, risk, benchmarks, financial and macro data, and the statistics the models use.

No sessions on Oct 9, Nov 20, or Nov 27. Most sessions are in 3007 BIF; sessions 1 and 3 are not.