Prompt Engineering
Neural Network Foundations
Transformer Architecture Basics
Encoder-Decoder Structure
Self-Attention Mechanisms
Multi-Head Attention
Feed-Forward Networks
Layer Normalization
Positional Encoding
Token Concept and Definition
Tokenization Methods
Subword Units
Byte Pair Encoding
Token Limits and Context Windows
Implications for Prompt Design
Next-Token Prediction
Probabilistic Nature of Generation
Sampling Methods
Greedy Decoding
Top-k Sampling
Top-p Nucleus Sampling
Temperature Control
Beam Search
Instruction Following Capabilities
Sensitivity to Prompt Phrasing
In-Context Learning
Few-Shot Learning Abilities
Emergent Abilities
Complex Reasoning Capabilities
Multi-Step Problem Solving
Knowledge Retrieval and Application
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1. Introduction to Prompt Engineering
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3. Core Components of Effective Prompts