Generative AI Foundations

This unit introduces core concepts, capabilities, and workflows of generative AI and prompt engineering, surveying major providers, model types, and common use cases across writing, visual, and enterprise contexts. Students will develop practical prompting and evaluation skills, learn how to combine and tailor models for specialized tasks, and identify ethical, legal, and interoperability considerations to prepare for applied and advanced units.

Learning Objectives

• Analyze the generative AI ecosystem by comparing major providers, model types, and deployment options against specific technical and business requirements for a given task.
• Apply prompt engineering techniques and structured workflows to produce targeted outputs (text and image) for academic, creative, and domain-specialized scenarios, demonstrating iterative improvement across at least two model variants.
• Evaluate generative AI outputs and models using defined criteria (accuracy, originality, bias, privacy risk, and fit for purpose) and recommend mitigation or selection strategies for enterprise or educational use cases.
• Demonstrate responsible human–AI collaboration by producing, refining, and documenting a short multimodal artifact (e.g., summarized report with visuals) that follows ethical, legal, and interoperability best practices.