Prompt Engineering: Techniques and Best Practices

Introduction to AI Language Models and Prompt Engineering

• Overview of AI language models
• Introduction to Prompt Engineering
• Importance of Prompt Engineering in AI applications

Understanding the Prompt

• Types of prompts
• Components of a prompt
• Factors affecting prompt effectiveness

Techniques for Crafting Effective Prompts

• Designing prompts for clarity
• Leveraging context and examples
• Balancing brevity and detail

Restricting ChatGPT’s Answers to Your Own Document Corpus

• Setting up a custom document corpus
• Techniques for guiding AI model focus
• LLM focus and attention, and GPT3 vs GPT4 differences
• Ensuring relevant and accurate outputs

Generating Synthetic Data and Images

• Crafting prompts for CSV data generation
• Formatting AI outputs for data visualization
• Prompt engineering for SVG image generation
• GPT4 SVG images vs DALL-E image generation

Language Translation and Slide Creation

• Designing prompts for language translation
• Ensuring translation accuracy and fluency
• Generating slides using markdown and Prompt Engineering

Prompt Engineering for Various Applications

• Creative writing and content generation
• Question-answering and information retrieval
• Data processing and transformation

Iterative Prompt Refinement

• Analyzing AI model outputs
• Techniques for prompt iteration and improvement
• Incorporating user feedback into prompt design

Group Project: Applying Prompt Engineering to Real-world Scenarios

• Identify a problem that can be solved using AI language models
• Design and refine prompts to achieve desired outcomes
• Present project outcomes and Prompt Engineering process

Ethics and Best Practices in Prompt Engineering

• Ethical considerations for AI language model usage
• Ensuring data privacy and security
• Best practices for Prompt Engineering in professional settings