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
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.
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
