This course, offered by MIT, provides an in-depth exploration of foundation models and Generative AI, covering both theoretical foundations and practical applications. It begins with an introduction to the field, explaining the evolution of large-scale AI models, their underlying architectures, and how they are trained to perform tasks across multiple domains.

Learners will gain a detailed understanding of how foundation models work, including LLMs like ChatGPT, text and image generation models, and their role in AI ecosystems. Practical topics include image generation, AI for biology and scientific research, and applications of autonomous systems powered by Generative AI. The course also examines the broader ecosystem of AI, exploring model interactions, deployment strategies, and integration into real-world applications.

Ethics and responsible AI use are emphasized throughout, providing learners with guidance on fairness, bias, and safety considerations in deploying foundation models. By the end of the course, participants will have a strong conceptual and practical understanding of Generative AI and foundation models, equipping them to leverage these technologies in research, industry, and innovation-driven projects.