Discovery Day- Intro to Prompt Engineering

In this course, you will learn how to create and optimize prompts for a variety of generative AI models. First, this course covers the basics of foundation models, including a subset of foundation models (FMs), called large language models (LLMs). Then, the course covers the fundamental concepts of prompt engineering, such as the different elements of a prompt and some general best practices for using prompts effectively. Finally, the course provides information about basic prompt techniques, including zero-shot, few-shot, and chain-of-thought (CoT) prompting.

Who Can Benefit

• This event is intended for:
• Prompt engineers
• Data scientists
• Developers

Skills Gained

• During this event, you will learn:
• Identify the fundamental concepts of FMs and LLMs
• Define prompt engineering and identify the best practices for designing effective prompts
• Identify the basic types of prompt techniques, including zero-shot, few-shot, and CoT techniques

Course Content

Module 1: Foundation models and large language models

• How does a foundation model function?
• Training FMs
• Types of FMs
• Large language models
• Transformer architecture
• Neural networks
• LLM use cases

Module 2: Key concepts of prompt engineering

• Fine-tuning and prompt engineering
• Elements of a prompt
• Best practices for designing effective prompts
• Practice with prompts

Module 3: Basic prompt techniques

• Zero-shot prompting
• Few-shot prompting
• Chain-of-thought prompting