Useful Links
1. Introduction to Prompt Engineering
2. Fundamentals of Large Language Models
3. Core Components of Effective Prompts
4. Basic Prompting Techniques
5. Crafting High-Quality Prompts
6. Advanced Prompting Strategies
7. Prompt Engineering Workflow
8. Task-Specific Applications
9. Security and Safety Considerations
10. Performance Evaluation and Optimization
11. Advanced and Emerging Topics
  1. Computer Science
  2. Artificial Intelligence

Prompt Engineering

1. Introduction to Prompt Engineering
2. Fundamentals of Large Language Models
3. Core Components of Effective Prompts
4. Basic Prompting Techniques
5. Crafting High-Quality Prompts
6. Advanced Prompting Strategies
7. Prompt Engineering Workflow
8. Task-Specific Applications
9. Security and Safety Considerations
10. Performance Evaluation and Optimization
11. Advanced and Emerging Topics
  1. Fundamentals of Large Language Models
    1. High-Level Architecture Overview
      1. Neural Network Foundations
        1. Transformer Architecture Basics
          1. Encoder-Decoder Structure
            1. Self-Attention Mechanisms
              1. Multi-Head Attention
                1. Feed-Forward Networks
                  1. Layer Normalization
                    1. Positional Encoding
                    2. Tokenization and Text Processing
                      1. Token Concept and Definition
                        1. Tokenization Methods
                          1. Subword Units
                            1. Byte Pair Encoding
                              1. Token Limits and Context Windows
                                1. Implications for Prompt Design
                                2. Text Generation Process
                                  1. Next-Token Prediction
                                    1. Probabilistic Nature of Generation
                                      1. Sampling Methods
                                        1. Greedy Decoding
                                          1. Top-k Sampling
                                            1. Top-p Nucleus Sampling
                                              1. Temperature Control
                                                1. Beam Search
                                                2. Key Model Behaviors
                                                  1. Instruction Following Capabilities
                                                    1. Sensitivity to Prompt Phrasing
                                                      1. In-Context Learning
                                                        1. Few-Shot Learning Abilities
                                                          1. Emergent Abilities
                                                            1. Complex Reasoning Capabilities
                                                              1. Multi-Step Problem Solving
                                                                1. Knowledge Retrieval and Application

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                                                              3. Core Components of Effective Prompts

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