Generative AI Foundations and Prompting

This unit introduces core concepts, capabilities, and limitations of generative AI while grounding students in practical prompt strategies, creative workflows, and model evaluation. Learners explore provider landscapes, ethics and academic integrity, and techniques for combining and tailoring models to real-world text and visual tasks, preparing them for more advanced model customization and deployment in subsequent units.

Learning Objectives

• Analyze core generative AI concepts, model types, and provider offerings to distinguish capabilities, limitations, and appropriate use cases
• Apply prompt engineering techniques—including keyword crafting, chaining, and multi-model combinations—to produce targeted text and visual outputs for specific professional or creative scenarios
• Demonstrate responsible use by identifying ethical, legal, and academic integrity issues (e.g., bias, hallucination, attribution) and implementing mitigation strategies in example workflows
• Evaluate and select GenAI tools and workflows for specialized domains by assessing model fit, enterprise vs. consumer trade-offs, and integration requirements with other technologies