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 Duration 7 hours

Course Outline

Introduction to Prompt Engineering

  • Defining prompt engineering and its business relevance
  • Common use cases and their impact on operational efficiency
  • Understanding typical behaviors of language models

Key Principles of Effective Prompting

  • Incorporating clarity, context, constraints, and illustrative examples
  • Managing output length, structure, and tone
  • Identifying and avoiding common errors

Advanced Prompt Patterns and Templates

  • Using instruction-based and role-specific prompts
  • Employing chain-of-thought and step-by-step reasoning techniques
  • Leveraging few-shot examples and reusing standardized templates

Practical Prompting Workshops

  • Creating prompts for text summarization and rewriting
  • Developing prompts for data classification and extraction tasks
  • Real-time refinement of prompts based on model responses

Assessment and Optimization

  • Applying metrics and heuristics to gauge prompt effectiveness
  • Validating prompts through testing and edge-case analysis
  • Managing versions and documenting prompt modifications

Safety, Bias, and Responsible Usage

  • Identifying and addressing biased or unsafe model outputs
  • Implementing basic safety guardrails and content restrictions
  • Determining when human oversight is necessary

Conclusion, Resources, and Future Learning

  • Access to quick-reference templates and cheat sheets
  • Recommended reading materials and community platforms
  • Guidance on continuous practice and advanced learning paths

Requirements

  • Prior experience using web-based AI chat platforms
  • A foundational grasp of natural language concepts
  • An openness to iterative problem-solving methods

Target Audience

  • Novices aiming to improve their ability to interact effectively with AI systems
  • Product managers, content creators, and analysts looking to leverage AI tools
  • Professionals tasked with creating or reviewing AI-generated material

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