Applied Generative AI Techniques

This unit covers practical use of generative AI for creative and technical projects, including prompt engineering, multimodal content production, autonomous agents, and troubleshooting system integration. Students will also examine model families and training methods (including reinforcement learning and human-in-the-loop techniques) while evaluating ethical, legal, and safety considerations to prepare for advanced implementation and deployment.

Learning Objectives

• Analyze strengths, limitations, and appropriate use-cases of major generative model families and reinforcement learning approaches for creative and technical tasks
• Apply advanced prompt engineering, data formatting, and multimedia workflows to produce and refine text, audio, image, and mixed‑media outputs while integrating citations and references
• Evaluate ethical, safety, and security risks (including bias, hallucination, and IP concerns) and propose mitigation strategies that align with responsible AI practices
• Demonstrate integration and troubleshooting of GenAI tools and pipelines — including autonomous agents, API/software interoperability, and basic model adaptation or code translation — to deliver functioning project prototypes