Applied Generative AI Production

This unit focuses on advanced, practical skills for producing reliable, audience‑aware generative AI content and multimodal assets. Learners build on foundational concepts to apply prompt engineering, model selection, troubleshooting, and responsible-AI practices in preparation for a final synthesis and portfolio project in the subsequent unit.

Learning Objectives

• Analyze differences among generative AI models and agent options (capabilities, multimodal support, hallucination tendencies, and integration constraints) to select the most appropriate solution for a given task
• Apply advanced prompt engineering techniques—including use of examples, constraints, supplemental data, and optimization tips—to produce coherent long-form articles, website content, speeches, and multimodal outputs (images, sound, music) that match specified audience, tone, and style
• Demonstrate methods to ensure content integrity and system reliability by integrating citations and references, mitigating hallucinations and misleading outputs, troubleshooting freezes and software integration issues, and implementing responsible AI safeguards
• Evaluate readability, engagement, and market appeal of AI-generated content using rubrics and analytics, and iterate prompts and workflows to measurably improve quality and audience fit