Prompt Engineering Guide 🧠

Master the art of communicating with Large Language Models. From the basics of zero-shot and few-shot prompting to advanced techniques for building agentic systems.

Driptanil DattaSoftware Developer

Mar 202615 min read

Prompt Engineering Guide 🧠

Welcome to the comprehensive guide on Prompt Engineering. This series covers everything you need to know to get the most out of modern LLMs like GPT-4, Claude, and Gemini.

📚 Course Modules

🚀Basics of Prompting ⚙️LLM Settings 🧩Prompt Elements 💡General Tips 📝Prompt Examples

Prompting Techniques

Advanced methods to improve reasoning, formatting, and reliability of large language models.

🎯Zero-Shot Prompting 🏗️Few-Shot Prompting 🧠Chain-of-Thought 🧩Meta Prompting ⚖️Self-Consistency 📚Generated Knowledge 🔗Prompt Chaining 🌳Tree of Thoughts 🔍RAG 🛠️ART 🤖APE ⚡Active-Prompt 🎯DSP 🐍PAL 🎭ReAct 🧠Reflexion 👁️Multimodal CoT

What We'll Cover

Prompt Fundamentals: Understanding zero-shot, few-shot, and role-based prompting.
Advanced Techniques: Chain-of-Thought, ReAct, and Instruction Tuning.
LLM Settings: Mastering temperature, top-p, and frequency penalties.
Building Agents: Leveraging tool use and function calling to create agentic systems.
Evaluation & Security: Measuring prompt performance and defending against prompt injection.

Position Explorations 🔍LLM Settings