Foundation models and generative AI

CS-461

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Course summary


Week 1: Introduction and Overview


Week 2: Learning at Scale: Supervised, Self-Supervised, and Beyond


Week 3: Generative Models I: Autoregressive, Adversarial, and Autoencoder Models


Week 4: Generative Models II: Diffusion Models and Beyond


Week 5: Tokenization Across Modalities and Building Blocks


Week 6: Architectures I: Language and Vision Foundation Models


Week 7: Semester Break


Week 8: Language FMs Continued


Week 9: Architectures II: Foundation Models in the Sciences


Week 10: Multimodality in Foundation Models


Week 11: Adaptation, Fine-Tuning, and Test-Time Training


Week 12: World Models and Generative World Modeling


Week 13: Architectures III: Foundation Models in Robotics


Week 14: Foundation Models, Reinforcement Learning, Reasoning, and Decision-Making


Week 15: Foundation Models and Agentic Systems and a Look into the Future


Recap Session for the Exam