What you'll learn

Most people struggle with AI because vague and inefficient prompts produce inconsistent results. In this course, Prompt Engineering Best Practices, you’ll learn to design structured, effective prompts that consistently generate high-quality outputs across tools like ChatGPT, Copilot, Gemini, and Perplexity AI. First, you’ll explore how language models actually interpret prompts, including the token mindset, context management, and the importance of clarity and cost awareness. Next, you’ll discover reusable prompt formulas, persona-driven “Act As” techniques, iterative refinement, prompt chaining, and reasoning strategies like Chain of Thought and ReAct. Finally, you’ll learn how to apply these methods in advanced workflows, from creative text and image generation to coding assistants and enterprise-scale use, as well as how to debug prompts, test variations, and apply ethical guardrails. When you’re finished with this course, you’ll have the skills and knowledge of prompt engineering needed to save time, improve accuracy, and confidently use prompting as a professional skill across creativity, coding, and enterprise applications.