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ChatGPT Basics

This ChatGPT training course will teach you the fundamentals of prompt engineering for large language models (LLMs). You will learn how to craft effective prompts to guide LLMs to generate the...

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$775 USD
Course Code WA3403
Duration 1 day
Available Formats Classroom, Virtual

This ChatGPT training course will teach you the fundamentals of prompt engineering for large language models (LLMs). You will learn how to craft effective prompts to guide LLMs to generate the desired output. You will also learn about different prompting techniques, including zero-shot prompting, few-shot prompting, chain-of-thought prompting, and retrieval augmented generation.

Skills Gained

  • Understand the basics of prompt engineering and its importance for LLMs
  • Identify the factors that affect prompt effectiveness
  • Learn different ways of structuring prompts and using examples
  • Explore advanced prompting techniques, such as zero-shot prompting, few-shot prompting, chain-of-thought prompting, and retrieval augmented generation
  • Apply prompt engineering to real-world scenarios in a group project
  • Understand the security risks and ethical considerations associated with prompt engineering

Who Can Benefit

This ChatGPT course is ideal for anyone who wants to learn how to use prompt engineering to get the most out of LLMs. It is especially relevant for researchers, developers, and other professionals who use LLMs for tasks such as content generation, machine translation, and code generation.

Prerequisites

No prior experience is presumed.

Course Details

Course Outline

Chapter 1: Understanding the Prompt

  • The Basics
  • Pitfalls
  • Highlighted Techniques
  • Understanding the Limitation

Chapter 2: Introduction to Large Language Models

  • Historical Context
  • How did LLM’s (Large Language Models) Evolve
  • Trends in LLM’s
  • Today’s Cloud and Offline LLM’s
  • How LLM’s Work
  • LLM Use Cases
  • The Importance of Prompt Engineering

Chapter 3: Techniques for Crafting Effective Prompts

  • Factors affecting prompt effectiveness
  • Ways of structuring prompts
  • Prompting with examples

Chapter 4: Advanced Prompting Techniques

  • Zero-Shot Prompting
  • Few-Shot Prompting
  • Chain-of-Thought Prompting
  • Combining Multiple Techniques
  • Self Consistency Prompting
  • Generated Knowledge Prompting
  • Tree of Thought Prompting
  • Automated Prompt Engineering
  • Retrieval Augmented Generation

Chapter 5: Group Project: Applying Prompt Engineering to Real-world Scenarios

  • Real World Scenarios
  • Group Project

Chapter 6: Ethics and Best Practices in Prompt Engineering

  • Security Risks with LLM’s
  • Obscuring Data for Privacy and Security
  • LLM Best Practices for Enterprise
  • Best Practices, Limitations, other Considerations

Conclusion

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