Selected course
Intelligent Agents
AI 221
Theory and practice of autonomous agents that perceive, reason, plan and act in complex environments.
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Academics
Building Intelligent Systems
Machine learning, deep learning, language models, agents and the foundations of artificial general intelligence.
Areas of study
Machine Learning
Models, data and generalization.
Deep Learning
Neural networks and representation learning.
Language Models
Architecture, training and alignment.
AI Agents
Reasoning, planning and tool use.
Multimodal Systems
Vision, language, audio and beyond.
AI Safety
Robustness, alignment and responsible deployment.
In this course
- Agent loops, planning and memory
- Tool use and retrieval
- Evaluation harnesses and baselines
- Agent security and least privilege
Assessment
Problem sets 25% · Closed-book examination 30% · Implementation or research project 35% · Oral defense 10%. Pass requires 80% on the examination and defense, 85% on problem sets and the project.
