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 Duration 7 hours

Course Outline

Introduction to Prompt Engineering

  • Defining prompt engineering and its importance
  • Common use cases and productivity impacts
  • An overview of typical model behaviors

Fundamental Principles of Effective Prompts

  • Clarity, context, constraints, and illustrative examples
  • Managing output length, format, and style
  • Identifying common pitfalls and strategies to avoid them

Prompt Patterns and Templates

  • Instructional prompts and role-playing prompts
  • Chain-of-thought and sequential step-by-step prompting
  • Few-shot examples and the reuse of templates

Practical Prompting Exercises

  • Creating prompts for summarization and text rewriting
  • Developing prompts for classification and data extraction tasks
  • Live refinement: adjusting prompts based on generated outputs

Assessing and Enhancing Prompts

  • Key metrics and heuristics for evaluating prompt quality
  • Employing tests and edge cases to verify prompt effectiveness
  • Tracking versions and documenting prompt modifications

Safety, Bias, and Responsible Usage

  • Detecting and mitigating biased or unsafe outputs
  • Implementing basic guardrails and content restrictions
  • Determining when human review is necessary

Conclusion, Resources, and Future Steps

  • Essential reference templates and quick guides
  • Suggested reading materials and community resources
  • Recommendations for ongoing practice and learning trajectories

Requirements

  • Experience with web-based AI chat interfaces
  • Foundational knowledge of natural language concepts
  • A willingness to engage in iterative problem-solving

Target Audience

  • Newcomers aiming to learn how to communicate effectively with AI models
  • Product managers, content creators, and analysts exploring AI tools
  • Professionals responsible for creating or reviewing AI-generated material

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