Course Overview
TOPIn 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.
Scheduled Classes
TOPWhat You'll Learn
TOPIdentify 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
- During this event, you will learn:
Outline
TOP
Viewing outline for:
How does a foundation model function?
- Training FMs
- Types of FMs
- Large language models
- Transformer architecture
- Neural networks
- LLM use cases
- Fine-tuning and prompt engineering
- Elements of a prompt
- Best practices for designing effective prompts
- Practice with prompts
- Zero-shot prompting
- Few-shot prompting
- Chain-of-thought prompting
Prerequisites
TOPWho Should Attend
TOPPrompt engineers
- Data scientists
- Developers
- This event is intended for:
