Catalog Description
Introduction to software engineering in the age of AI. Strengthen existing Python, learn classic engineering practice, and then augment it with large language models, retrieval-augmented generation, and agents. Design scalable, reliable distributed systems, learning from real architectures such as Amazon and Netflix, and designing AI-powered systems themselves.
Instructor Description
AI-Augmented Software Engineering and System Design weaves four strands into one 13-week course. Week 1 gives every student the same engineering-grade Python foundation: classes, dataclasses, typing, testing, HTTP, and async; core Python is a self-study prerequisite checked by a diagnostic. Weeks 2 and 3 cover standard software engineering: process, requirements, design principles, testing, code review, CI/CD, and maintenance. Weeks 4 to 8 augment that practice with AI: how language models work, context engineering and spec-driven development, verification of generated code, retrieval and RAG, agents and sandboxes, research methods and benchmarks, and security and responsible use. Weeks 9 to 13 turn to system design: estimation, networking and APIs, caching, data and storage, distributed systems, and a case-study class on real systems such as Amazon and Netflix, then LLM and RAG systems at scale.
Prerequisites
Graduate standing.
Restrictions
Enrollment in Information Studies (INF) courses is restricted to graduate students in the School of Information through registration periods 1 and 2, with outside students only being accepted during period 3.
Current and Upcoming Classes for this Course
| Class Name | Semester | Day(s) | Start Time(s) | End Time(s) | Building | Room |
|---|---|---|---|---|---|---|
| INF 385T: Special Topics in Information Science: AI Augmented Software Engineering and System Design
Shounak Roychowdhury |
Spring Term 2027 |
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