AI Atlas
A 10-week introductory course that provides a comprehensive foundation in generative artificial intelligence. Students will learn core concepts, techniques, and applications of generative models including large language models, diffusion models, and GANs. The course covers both theoretical foundations and practical implementation, with emphasis on understanding how these models work, their capabilities and limitations, and how to apply them responsibly. Topics progress from basic generative modeling principles to advanced applications including text generation, image synthesis, and multimodal AI systems.
Foundations of Generative AI
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prerequisite relationship
Generative Models and Probability -> Autoregressive Generation Fundamentals
Generative Models and Probability appears earlier in the syllabus and supports Autoregressive Generation Fundamentals.