Generative AI

Catalog description

By leveraging deep learning models, Generative AI is redefining content generation and enhancement, driving breakthroughs in text generation, image synthesis, music composition, video production, and software development. This course provides a comprehensive introduction to the fundamentals, architectures, and applications of modern Generative AI. Students will explore core generative models such as VAEs, GANs, Diffusion Models, and Transformers, as well as cutting-edge applications in large language models (LLMs), Retrieval-Augmented Generation (RAG), and multimodal AI. Through hands-on programming assignments and projects, students will gain experience in fine-tuning and deploying generative models, reinforcement learning for generative AI (RLHF), and prompt engineering to optimize AI outputs. The course also covers ethical considerations and responsible AI practices, ensuring students understand both the potential and the risks of AI-generated content. By the end of the course, students will be equipped with the knowledge and practical skills to build, customize, and ethically apply Generative AI in real-world scenarios