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Starts 25 June 2025 06:48

Ends 25 June 2025

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Prompt Engineering for Claude

Join the course "Prompt Engineering for Claude" on Pluralsight and dive deep into advanced techniques that optimize interactions with Claude Sonnet. This course is designed for those aiming to master the workbench interface and learn the art of crafting precise contexts and instructions. Elevate your AI projects by constructing examples that ef.
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Overview

Prompt engineering is one of the most significant new engineering specialties to occur in technology, business, and society at large. In this course, Prompt Engineering for Claude, you’ll learn to leverage Claude Sonnet’s impressive capabilities as a hybrid reasoning model through powerful approaches to prompt engineering.

First, you’ll get familiar with the feature rich workbench and API interfaces that allow development with Claude. Next, you’ll discover how to construct context, instructions and examples to reliably guide Claude’s responses to best meet your needs.

Including techniques such as feedback, examples, context, and breakdown. Finally, you’ll learn how to assess and improve the effectiveness of your responses using temperature, token limits, and Claude’s newest feature extended thinking.

When you’re finished with this course, you’ll have the skills and knowledge needed to develop LLM powered agents, interfaces, tools, or even your own code with Claude.

Syllabus

  • Introduction to Prompt Engineering for Claude
  • Overview of Claude Sonnet’s capabilities and applications
    Importance of prompt engineering in technology and business
  • Understanding Claude’s Workbench and API Interfaces
  • Features and functionalities of the workbench
    Navigating and utilizing the API for development
  • Constructing Effective Prompts
  • Developing context, clear instructions, and illustrative examples
    Techniques for guiding Claude’s responses
    Feedback mechanisms
    Use of examples and scenarios
    Contextual breakdown for complexity management
  • Techniques for Optimizing Claude’s Performance
  • Utilizing temperature settings for response variability
    Managing token limits for efficiency
    Leveraging Claude’s extended thinking capabilities
  • Evaluating and Refining Prompt Effectiveness
  • Metrics for assessing response quality and relevance
    Iterative improvement of prompt strategies
  • Case Studies and Practical Applications
  • Developing LLM powered agents and interfaces
    Creating tools and generating code with Claude
  • Summary and Course Conclusion
  • Recap of key concepts and techniques
    Where to go next: further learning and resources

Taught by

Russ Thomas


Subjects

Computer Science