Mastering Zero-Shot & Few-Shot Prompting in LLMs

Categories: Prompt Engineering
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Course Content

Understanding LLMs Architecture & Prompt Behavior

  • Transformer Architecture का परिचय
  • Attention Mechanism को सरल भाषा में समझना
  • Tokenization और Context Window की सीमाएँ
  • Prompt Input से Output तक की प्रक्रिया
  • Language Modeling Objectives (Causal vs Masked)
  • Pre-training और Fine-tuning का अंतर
  • Instruction Tuning क्या है और क्यों जरूरी है
  • In-context Learning: Core Mechanism
  • Temperature, Top-k, Top-p Sampling Explained
  • Prompt Drift और Output Instability
  • Prompt Behavior और Latent Representations

Zero-shot Prompting – Theory to Real-World Use

Few-shot Prompting with Exemplars

Case Studies – Prompting in Action

Refinement, Bias Reduction & Prompt Debugging

Templates, Practice Sets & Assignments

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