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 Duration 7 hours

Course Outline

Fundamentals of Prompt Engineering

  • Defining prompt engineering and explaining its importance
  • Exploring typical use cases and their effect on efficiency
  • Summarizing standard model behaviors

Key Elements of High-Impact Prompts

  • Incorporating clarity, context, constraints, and examples
  • Managing output length, formatting, and stylistic tone
  • Identifying common mistakes and strategies to prevent them

Effective Prompt Patterns and Templates

  • Using instruction-based and role-based prompts
  • Implementing chain-of-thought and sequential prompting techniques
  • Leveraging few-shot examples and reusable templates

Practical Prompting Workshops

  • Developing prompts for content summarization and revision
  • Creating prompts for data categorization and extraction tasks
  • Refining prompts in real-time based on generated outputs

Assessing and Optimizing Prompts

  • Applying metrics and heuristics to gauge prompt effectiveness
  • Validating prompts using tests and edge cases
  • Managing version control and documenting prompt modifications

Safety, Bias, and Ethical Considerations

  • Identifying and reducing biased or unsafe content
  • Establishing basic safety guardrails and content limits
  • Determining when human oversight is required

Conclusion, Resources, and Future Pathways

  • Accessing quick-reference guides and summary sheets
  • Exploring recommended literature and community resources
  • Pursuing continued practice and advanced learning tracks

Requirements

  • Proficiency with web-based AI chat platforms
  • Foundational knowledge of natural language concepts
  • Adeptness in iterative problem-solving processes

Target Audience

  • Novices seeking to improve their communication with AI models
  • Product managers, content specialists, and analysts investigating AI capabilities
  • Professionals tasked with creating or assessing AI-generated material

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