Short Course: An Overview of LLMs for Statisticians: Foundations, Reasoning, and Agentic AI

George Washington University’s Department of Statistics presents a full-day short course led by Rutgers statistician Linjun Zhang. It is designed for statisticians and data scientists who want a rigorous but practical view of contemporary large language models.

The programme starts with embeddings, transformers and the model-training pipeline, including pretraining, parameter-efficient fine-tuning and reinforcement learning from human feedback. It then turns to reasoning models and agentic AI, with context and harness engineering, agent design, safety, reliability and evaluation. Practical examples and hands-on activities are part of the course.

The session takes place in room B17 at 1957 E Street NW, with a lunch break from noon to 1:30 PM. The official GW ticket page showed a $200 registration option when verified.