AI and Machine Learning Trainin

by Web Age Solutions team Claim Listing

Learn how to craft effective prompts to guide large language models to generate the desired output with this comprehensive course on getting the most out of ChatGPT.

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img Duration

1 Day

Course Details

Learn how to craft effective prompts to guide large language models to generate the desired output with this comprehensive course on getting the most out of ChatGPT.

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.

 

Objectives

  • 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

 

Prerequisites

No prior experience is presumed.

 

Audience

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.

 

Outline for ChatGPT Basics Training

  • 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

  • Toronto Branch

    220 Yonge Street Suite 218B, Toronto

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