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

11Evaluation, Metrics, and Quality Control

12Safety, Ethics, and Risk Mitigation

Harmful Content Avoidance Bias and Fairness Controls Privacy and PII Handling Copyright and Licensing Hallucination Containment Verification Before Action Domain-Specific Risk Patterns Prompt Injection Awareness Jailbreak Resistance Strategies Secure Delimiters and Sandboxing Sensitive Topic Handling Consent and User Safeguards Age-Appropriate Design Transparency and Disclosure Accountability and Audit Trails

13Tools, Functions, and Agentic Workflows

14Retrieval-Augmented Generation (RAG)

15Multimodal and Advanced Prompt Patterns

Courses/Generative AI: Prompt Engineering Basics/Safety, Ethics, and Risk Mitigation

Safety, Ethics, and Risk Mitigation

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Build safe prompts that reduce harm, protect privacy, handle sensitive content, and maintain accountability.

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Sensitive Topic Handling

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