Building Advanced Generative AI Systems

Catalog description

Hands-on coding skills necessary to design, implement, and deploy advanced Generative AI systems. Emphasizes the technical development of AI architectures and coding proficiency, with a focus on foundational and advanced topics, including Retrieval-Augmented Generation (RAG), agentic systems, and model fine-tuning. Using Python and Jupyter Notebooks, students will develop and iterate upon real-world generative AI applications, progressing from building RAG models to fine-tuning and deploying AI systems in production. Key technical areas include embedding techniques, vector database integration, prompt engineering, and establishing agentic workflows. Balances coding exercises with project-based learning to reinforce the skills needed to engineer high-performing Generative AI systems.