The LLM Agents MOOC (Fall 2024) introduces students to large language models and their use in building autonomous agents. It covers foundations of LLMs, prompt engineering, tool integration, multi-agent systems, and real-world applications. The course blends theory with hands-on projects, preparing learners to design intelligent, adaptive AI systems.

Language models serve as the cornerstone of modern natural language processing (NLP) applications and open up a new paradigm of having a single general purpose system address a range of downstream tasks. As the field of artificial intelligence (AI), machine learning (ML), and NLP continues to grow, possessing a deep understanding of language models becomes essential for scientists and engineers alike. This course is designed to provide students with a comprehensive understanding of language models by walking them through the entire process of developing their own. Drawing inspiration from operating systems courses that create an entire operating system from scratch, we will lead students through every aspect of language model creation, including data collection and cleansing for pre-training, transformer model construction, model training, and evaluation

This graduate‑level course explores deep generative models, including autoregressive methods, VAEs, GANs, normalizing flows, energy‑based models, and diffusion approaches. Through 18 detailed lectures, students gain theoretical foundations and practical insights into model design, training, and evaluation. It equips learners to understand, analyze, and innovate within modern generative AI research.