1. Introduction to Prompt Engineering
• What is prompt engineering and why it matters
• Real-world examples in business, marketing, HR, operations
• Capabilities and limitations of LLMs (like ChatGPT, Claude, Gemini)

2. Understanding the Basics
• Types of prompts: System vs. User
• Structure of a good prompt
• Few-shot, zero-shot, and chain-of-thought prompting
• RACE Framework of Prompt
• Role prompting: setting context for better results

3. Prompting Techniques for Common Tasks
• Summarizing emails, reports, and meetings
• Drafting professional content: emails, SOPs, LinkedIn posts
• Generating ideas, outlines, and presentations
• Rewriting and simplifying complex content

4. Improving Prompt Effectiveness
• Tone, format, and length control
• Using tables, bullet points, and sections
• Getting better output through step-by-step instructions
• Iterating and refining prompts

5. Use Cases by Department
• Marketing: ad copy, social posts, blog ideas
• HR: job descriptions, interview questions, policy summaries
• Sales: pitch drafting, email follow-ups, objection handling
• Finance: summarizing reports, variance commentary

6. Using Prompt Libraries and Templates
• How to reuse and adapt effective prompts
• Storing prompt templates in Google Docs / Notion
• Community libraries and best prompt repositories

7. GenAI Tools with Built-in Prompt Interfaces
• Overview: ChatGPT, Gemini, Claude, Perplexity
• When to use what: strengths and special features
• Voice and image prompts (multimodal prompts)

8. Ethics, Accuracy & AI Validation
• Avoiding hallucinations and bias
• Checking facts and ensuring data privacy
• When not to trust AI: guardrails for professionals

9. Mini Projects and Capstone
• Use a prompt to automate a weekly task
• Create a personal prompt library
• Present a real-world use case with your optimized prompts