Prompt Engineering with Llama 2 & 3 - Syllabus

• Introduction
  • Introduction to Llama 2 & 3 models and their applications in prompt engineering
  • Course objectives and key concepts
• Overview of Llama Models
  • Introduction to Meta's Llama 2, Llama 3, Code Llama, and Llama Guard models
  • Differences and applications for each model
• Getting Started with Llama 2 & 3
  • Making API calls to interact with Llama models
  • Basic usage examples and output differences
• Multi-turn Conversations
  • Implementing conversations that retain context across turns
  • Examples of complex, multi-turn dialogues
• Prompt Engineering Techniques
  • Few-shot prompting for sentiment classification
  • Chain-of-thought prompting for logic problems
• Comparing Different Llama 2 & 3 Models
  • Evaluating and comparing responses from various Llama models
  • Choosing the appropriate model for specific tasks
• Code Llama
  • Using Code Llama as a pair programming partner
  • Learning to write and improve code with Llama's assistance
• Llama Guard
  • Ensuring safe and responsible AI usage with Llama Guard
  • Filtering harmful or inappropriate content
• Walkthrough of Llama Helper Function (Optional)
  • Overview of helper functions for Llama interactions
  • Hands-on example for implementing helper functions
• Conclusion
  • Recap of key concepts and prompt engineering techniques
  • Best practices for using Llama models in real-world applications