Learners explore the fundamentals of prompt engineering for generative Al tools by learning how to craft prompts that guide systems to produce relevant, creative, and accurate outputs. Emphasis is placed on understanding how language, intent, and structure influence Al behavior and outcomes across a range of applications, from written communication and content generation to analysis and decision-making. Through guided activities, learners practice writing, troubleshooting, and adapting prompts for use in communication, content creation, productivity, and analysis. Emphasis is placed on understanding how input shapes output, how language influences Al responses, and how to balance human creativity with Al automation. Using frameworks such as PTCF (Persona, Task, Context, Format), ROSES (Role, Objective, Steps, Examples, Style), RAIC (Role, Audience, Intent, Context), IDEAL (Intent, Details, Examples, Audience, Limitations), learners develop and refine prompts across multiple formats and platforms. They examine how prompt engineering supports human-Al collaboration, improves efficiency, and contributes to ethical, transparent, and responsible Al use. From shaping Al-generated visuals to addressing bias and misinformation, learners gain practical insight into the evolving role of AI in communication, research, and creative work.
This is one of two foundational courses in the occupation-specific Artificial Intelligence (AI) series of courses. It is strongly recommended that students have a mastery of competencies usually obtained by completing AI Prompt Engineering (ONT AI1), followed by Agentic AI (ONT AI2), before proceeding with other occupation-specific courses in the series: AI for Entrepreneurs, AI for Marketing, AI for Human Resources, AI for Business Analysis.