Introduction to Prompt Engineering

Introduction to Prompt Engineering explores how the quality of AI-generated responses depends on the clarity, structure, and detail of the instructions provided. The course introduces learners to the foundations of prompt engineering and explains how effective prompts help Generative AI understand tasks, use relevant context, follow constraints, and produce more accurate and useful outputs. Through six focused lessons, learners explore the main components of a prompt, including role, task, context, constraints, examples, and output format. The course covers zero-shot, one-shot, few-shot, persona, structured-output, and chain-of-thought prompting, along with practical methods for refining, debugging, and improving weak prompts. Learners also examine best practices such as managing context, using delimiters, reducing hallucinations, recognising prompt-injection risks, and understanding the limitations of AI systems. In the final project, learners apply these skills to create an AI-powered study planner and compare the results of a basic prompt with an optimized version. Learning Outcomes: > Design clear, structured, and effective prompts. > Apply different prompting techniques to a variety of tasks. > Improve AI responses through refinement, debugging, and prompt chaining. > Evaluate AI outputs for accuracy, relevance, and completeness. > Build a practical AI-powered study planner. > Earn a certificate of completion.