Call Number | 10299 |
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Points | 1.5 |
Grading Mode | Standard |
Approvals Required | None |
Instructor | Mike Q Zhu |
Type | LECTURE |
Method of Instruction | In-Person |
Course Description | MIA and MPA Policy Skills II Core. Pre-reqs: Working Python knowledge OR Python for Public Policy (SIPA IA6650) OR Intro to Text Analysis in Python (SIPA IA6655). In the past two years, Large Language Models (LLMs) built using transformer frameworks have emerged as the fastest-growing area of research and investment in AI/machine learning. Recent releases of chatbots such as ChatGPT (OpenAI), Bing (Microsoft), and Bard (Google) quickly reached hundreds of millions of users and have become the face of artificial intelligence for consumers. There has also been an explosion in the number of applications that depend on LLMs for a variety of more specialized tasks. Recent models have shown impressive performance on both canonical machine learning tasks and for everyday use, yet are in many ways poorly understood and, in some cases, exhibit unexpected and potentially harmful behavior. Policymakers, analysts, and non-profit and industry leaders need an understanding of these models to take advantage of the opportunities they present and to mitigate potential harms. This course provides an overview of Large Language Models and gives students hands-on experience with various ways of interacting with LLMs. Students will learn to interpret model evaluation metrics, and we will discuss safety and ethics in applied contexts. |
Web Site | Vergil |
Department | Data Science for Policy |
Enrollment | 0 students (45 max) as of 9:05PM Friday, August 8, 2025 |
Subject | School of International & Public Affairs |
Number | IA6674 |
Section | 001 |
Division | School of International and Public Affairs |
Open To | SIPA |
Section key | 20261SIPA6674U001 |