Class Information
Time: Tuesdays, 5:15 PM - 6:45 PM
Location: Towne 337
Semester: Spring 2026
Description
Welcome to CIS-1990! In this course, you will learn how to practically instantiate and apply LLMs by designing intelligent, interactive agents. Moving beyond basic prompting, this course explores the full lifecycle of building LLM-powered applications, from reasoning and planning to extending capabilities with memory, retrieval, and tool integration. Through hands-on projects, you will learn techniques such as Retrieval-Augmented Generation (RAG) and multi-step agent design, while also addressing reliability and safety by diagnosing failure modes, implementing guardrails, and conducting systematic evaluations. The course culminates in a final project where you build and present your own LLM agent. Python proficiency is required, but no prior machine learning background is assumed.
Important Links
Course Schedule
| Week | Date | Lecture Topic | Homework |
|---|---|---|---|
| Module 1: Interacting with LLMs | |||
| 1 | Jan 20 | What is an Agent? A brief history of language modeling [slides] | [HW 1 Released] |
| 2 | Jan 27 | Snow Day! No Class | |
| 3 | Feb 3 | LLM architectures and training [slides] | HW 1 Due [HW 2 Released] |
| 4 | Feb 10 | How does an LLM generate text? [slides] [decoding.py] [answers] | |
| 5 | Feb 17 | Prompting, Reasoning, & Memory [slides] | HW 2 Due [HW 3 Released] |
| Module 2: Building an LLM Agent | |||
| 6 | Feb 24 | Post-training & Retrieval [slides] [RAG.py] [answers] | |
| 7 | Mar 3 | Prompt chaining, routing, and planning [slides] [planning.py] | HW 3 Due |
| - | Mar 10 | Spring Break - No Class | |
| 8 | Mar 17 | Tool Calling, Frameworks, & MCP [slides] [web_search.py] | [Final Project Proposal] |
| 9 | Mar 24 | AI safety [slides] | Project Proposal Due [Final Project] |
| 10 | Mar 31 | Vibe coding & agent evaluation [slides] | |
| Module 3: LLM Agents in the real world | |||
| 11 | Apr 7 | Guest Lectures: Open problems with LLM agents | |
| 12 | Apr 14 | Guest Lectures: Deploying LLM agents in industry | |
| 13 | Apr 21 | Office Hours: Final Project Q&A (attendance optional) | |
| 14 | Apr 28 | Final Project Presentations | Final Project Due |
Assignments & Grading
Assignments are due at 11:59 PM Eastern Time. Every student has 3 late days that may be used at their discretion across the semester; beyond this allowance, late work will not be accepted. Grades will be 35% homeworks, 45% final project, and 20% participation. Participation is based on attendance + contribution during class activities. You are allowed to miss class 2 times without penalty (otherwise you need to email me).
Course Staff
