Generative AI: Prompt Engineering Basics

Chapters

1Foundations of Generative AI

2LLM Behavior and Capabilities

3Core Principles of Prompt Engineering

4Writing Clear, Actionable Instructions

5Roles, Personas, and System Prompts

6Supplying Context and Grounding

7Examples: Zero-, One-, and Few-Shot

8Structuring Outputs and Formats

9Reasoning and Decomposition Techniques

10Iteration, Testing, and Prompt Debugging

Test Case Design A/B and Multivariate Prompt Tests Minimal Reproducible Prompts Error Pattern Analysis Prompt Ablation Studies Parameter Sweep Experiments Red Teaming for Robustness Guardrail Trigger Testing Fallback and Recovery Prompts Versioning and Naming Conventions Change Logs and Diffing Regression Test Suites Canary Questions and Probes Peer Review and Pair Prompting Capturing Learnings and Playbooks

11Evaluation, Metrics, and Quality Control

12Safety, Ethics, and Risk Mitigation

13Tools, Functions, and Agentic Workflows

14Retrieval-Augmented Generation (RAG)

15Multimodal and Advanced Prompt Patterns

Courses/Generative AI: Prompt Engineering Basics/Iteration, Testing, and Prompt Debugging

Iteration, Testing, and Prompt Debugging

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Develop a rigorous workflow to test, analyze, and refine prompts using experiments, versioning, and red teaming.

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Red Teaming for Robustness

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