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 Duration 7 hours

Course Outline

Introduction to Prompt Engineering

  • Defining prompt engineering and explaining its importance.
  • Exploring typical use cases and their impact on productivity.
  • An overview of standard model behaviors.

Core Principles for Effective Prompts

  • Integrating clarity, context, constraints, and examples.
  • Managing output length, structure, and tone.
  • Identifying common pitfalls and strategies to avoid them.

Prompt Patterns and Templates

  • Using instruction-based prompts and role-playing scenarios.
  • Applying chain-of-thought and step-by-step reasoning techniques.
  • Leveraging few-shot examples and reusable templates.

Practical Prompting Exercises

  • Creating prompts for summarizing and rewriting text.
  • Designing prompts for classification tasks and data extraction.
  • Real-time iteration: adjusting prompts based on model outputs.

Evaluating and Enhancing Prompts

  • Utilizing metrics and heuristics to gauge prompt quality.
  • Validating prompts through testing and edge-case scenarios.
  • Implementing version control and documentation for prompt changes.

Safety, Bias & Responsible Usage

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

Conclusion, Resources & Future Steps

  • Access to quick-reference templates and cheat sheets.
  • Curated reading lists and community resources.
  • Recommendations for ongoing practice and advanced learning paths.

Requirements

  • Basic familiarity with web-based AI chat interfaces.
  • Foundational understanding of natural language concepts.
  • Willingness to engage in iterative problem-solving.

Target Audience

  • Individuals new to AI who aim to communicate effectively with language models.
  • Product managers, content creators, and analysts looking to leverage AI tools.
  • Professionals responsible for creating or assessing AI-generated content.

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