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 Duration 7 hours

Course Outline

Introduction to Prompt Engineering

  • Defining prompt engineering and its importance.
  • Common use cases and their impact on productivity.
  • Understanding typical model behaviors.

Core Principles of Effective Prompts

  • Key elements: clarity, context, constraints, and examples.
  • Managing output length, format, and tone.
  • Identifying common pitfalls and strategies to avoid them.

Prompt Patterns and Templates

  • Utilizing instruction-based and role-based prompts.
  • Implementing chain-of-thought and step-by-step prompting techniques.
  • Leveraging few-shot examples and template reuse.

Hands-on Prompting Exercises

  • Creating prompts for summarization and rewriting tasks.
  • Developing prompts for classification and data extraction.
  • Live iteration: adjusting prompts based on real-time outputs.

Evaluating and Improving Prompts

  • Using metrics and heuristics to assess prompt quality.
  • Validating prompts through testing and edge cases.
  • Versioning and documenting prompt evolution.

Safety, Bias & Responsible Use

  • Identifying and mitigating biased or unsafe outputs.
  • Establishing basic guardrails and content restrictions.
  • Determining when human review is necessary.

Wrap-up, Resources & Next Steps

  • Quick-reference templates and cheat sheets.
  • Recommended reading materials and community resources.
  • Pathways for continued practice and further learning.

Requirements

  • Experience with web-based AI chat interfaces.
  • A foundational grasp of natural language concepts.
  • An appetite for iterative problem-solving.

Target Audience

  • Beginners eager to master effective communication with AI models.
  • Product managers, content creators, and analysts looking to integrate AI tools into their workflows.
  • Professionals responsible for creating or assessing AI-generated content.

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