Module 1: Introduction to Prompt Engineering

• What prompt engineering is
• Why prompting is a core AI skill
• Prompting across business and technical workflows
• Where prompting adds value in modern roles

Module 2: Understanding AI Response Behavior

• Prompt to response behavior
• Role of context and instructions
• Why outputs vary
• Common limitations and failure patterns

Module 3: Core Prompting Techniques

• Role-based prompting
• Step-by-step prompting
• Few-shot prompting
• Instruction structuring
• Constraints and output control

Module 4: Improving Prompt Quality

• Making outputs more accurate
• Reducing hallucinations and ambiguity
• Improving consistency and formatting
• Designing prompts for reliable reuse

Module 5: Advanced Prompt Design

• Multi-step prompts
• Prompt chaining
• Breaking complex problems into sub-prompts
• Building reusable prompt systems

Module 6: Prompt Evaluation and Optimization

• Evaluating outputs against goals
• Iterating and refining prompts
• Comparing alternative prompts
• Debugging failures systematically

Module 7: Prompting for Real-World Use Cases

• Content creation and rewriting
• Coding and debugging support
• Data handling and extraction
• Task automation and workflow support
• Research and business productivity use cases

Module 8: Responsible and Safe Prompting

• Data privacy awareness
• Safe use of sensitive information
• Reducing unsafe or misleading outputs
• Human review and validation practices

Module 9: Capstone Project

• Define a practical use case
• Design a prompt system with reusable templates
• Validate and optimize outputs
• Package results into a presentation-ready artifact