Prompt Engineering
This course is for developers who have completed the LLM Basic training and want to learn the systematic method of Prompt design and optimization. From basic concepts to advanced patterns, from manual design to automated tools, this course helps students master the complete skill system of Prompt Engineering and improve the effectiveness and reliability of LLM applications.
Day 1: Prompt Basics and Engineering Methods
From Trial and Error to Systematic Design
π Today's Content
1.1 Prompt Basic Concepts
What is a Prompt: definition, principle and key mechanism
Common types and basic structure of Prompts (Instruction, Input, Output, Constraints)
1.2 Introduction to Prompt Engineering
Why Prompt Engineering is needed: from trial and error to systematic design
The core goals and value of Prompt Engineering
Overview of application scenarios: product design, data processing, dialogue systems, code generation, etc.
How to systematically design and optimize Prompts
1.3 Construction Framework for Efficient Prompts
Analysis of common elements: Persona, Task, Context, Format
Case study: how to build a clear, efficient and robust Prompt from scratch
1.4 Tool Drills and Practical Operations
Use ChatGPT to experience the process of writing and tuning Prompts
Analysis of typical failure cases and optimization suggestions
π‘ Learning Objectives
- β In-depth understanding of the working principle and basic structure of Prompts
- β Master the systematic design method of Prompt Engineering
- β Learn to use the construction framework to design efficient Prompts
- β Accumulate experience in Prompt optimization through practical operations