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 Duration 7 hours

Course Outline

Introduction to Prompt Engineering

  • Defining prompt engineering and its significance
  • Common use cases and their impact on productivity
  • Overview of typical model behaviours

Core Principles of Effective Prompts

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

Prompt Patterns and Templates

  • Instruction-based and role-based prompts
  • Chain-of-thought and step-by-step prompting techniques
  • Few-shot examples and reusing templates

Hands-on Prompting Exercises

  • Creating prompts for summarisation and rewriting
  • Designing prompts for classification and data extraction
  • Live iteration: refining prompts based on output results

Evaluating and Improving Prompts

  • Metrics and heuristics for assessing prompt quality
  • Using tests and edge cases to validate prompts
  • Versioning and documenting prompt modifications

Safety, Bias & Responsible Use

  • Identifying and mitigating biased or unsafe outputs
  • Basic guardrails and content constraints
  • Determining when human review is necessary

Wrap-up, Resources & Next Steps

  • Quick reference templates and cheat sheets
  • Recommended reading and community resources
  • Suggestions for ongoing practice and learning paths

Requirements

  • Familiarity with web-based AI chat interfaces
  • A basic grasp of natural language concepts
  • Comfort with iterative problem-solving

Target Audience

  • Beginners eager to learn how to communicate effectively with AI models
  • Product managers, content creators, and analysts exploring AI tools
  • Individuals responsible for generating or evaluating AI-driven content

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