Prompt Engineering Course

Topics Covered:

• Frame and analyse complex “wicked problems” that have no single correct answer
• Apply zero-shot, few-shot, Persona Pattern, and conditional prompting techniques
• Use the Cognitive Verifier to challenge assumptions and uncover blind spots
• Apply Flipped Interaction techniques where AI acts as the interrogator
• Generate alternative perspectives using the Alternate Approach Pattern and Tree of Thought reasoning
• Expand promising ideas into structured strategy prototypes

Topics Covered:

• Apply Chain-of-Thought, Zero-Shot CoT, ReAct Prompting, and Task Decomposition for complex reasoning tasks
• Refine prompts using Question Refinement and reasoning transparency techniques
• Evaluate outputs using LLM Grading, comparative audits, and blind spot stress testing
• Build reusable prompt systems using Template Patterns, placeholders, and structured blueprints
• Apply Fact Check Lists and Claim Check methods to improve output reliability
• Design Root Prompts, Context Injection frameworks, and Semantic Filters to establish AI guardrails

Topics Covered:

• Compare ChatGPT and Claude behaviours across different task types and use cases
• Configure model parameters including temperature, tokens, and penalties
• Apply Game Play Patterns and Scenario Simulations to test AI decision-making
• Design multi-turn prompt strategies using Tail Generation, Prompt Chaining, and session continuity techniques
• Build an integrated prompt system combining prompting patterns, reasoning frameworks, verification methods, and AI guardrails
• Present a complete prompt engineering solution for a real-world business challenge

• Case Study Written Assessment
• Individual Project Presentation