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Learners explore the fundamentals of prompt engineering for generative AI 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 AI 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 AI responses, and how to balance human creativity with AI 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-AI collaboration, improves efficiency, and contributes to ethical, transparent, and responsible AI use. From shaping AI-generated visuals to addressing bias and misinformation, learners gain practical insight into the evolving role of AI in communication, research, and creative work.
This course is delivered Online Asynchronously. For more information on the delivery methods, click here.
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