Generative AI

Catalog description

This course provides a graduate-level introduction to Generative AI, covering foundational concepts, architectures, and applications. The course will explore key topics, including Prompt Engineering, transformers, diffusion models, and overview of Fine-tuning LLM. This course will strongly focus on Agentic AI and building LLM powered applications. The course also covers the security concerns of Generative AI. Students will gain hands-on experience through labs and the final project that requires the students to develop an application integrating LLM to solve a practical problem. In this project the student will develop problem identification and problem-solving skills training the students to workforce/academia. Course Learning Outcomes 1. Demonstrate the understanding of foundations of generative AI including transformers, and diffusion models. 2. Demonstrate the skills in basic prompt engineering techniques. 3. Implement Agentic AI Systems – understand and build agentic AI systems (e.g., ReAct) that integrate LLMs with APIs. 4. Develop analytical thinking skills and ability to discuss about the ethical and societal implications of Generative AI. 5. Develop an application using LLM to solve a real-world problem. View Class Schedule