How LLMs Work? | Prompt Engineering For Developers Ep 02 | Large Language Models Explained | LLM

How LLMs Work? | Prompt Engineering For Developers Ep 02 | Large Language Models Explained

Welcome to My Digital Diaries - English 🚀

This is Episode 02 of the Prompt Engineering For Developers series.

In this video, we break down How LLMs (Large Language Models) Work — the technology behind ChatGPT, Generative AI, and modern AI applications.

If you're a Developer, AI Engineer, or Tech Enthusiast, understanding how LLMs work will help you:

✔️ Write Better Prompts
✔️ Build AI Powered Applications
✔️ Understand Generative AI Fundamentals
✔️ Improve Developer Productivity

📌 What You'll Learn in This Video

• What is an LLM (Large Language Model)
• Transformer Architecture Explained
• What is Token & Tokenization
• Context Window Explained with Example
• Training vs Prompting
• Limitations of LLMs
• What to Learn Next

📌 Timestamps

00:00 – Introduction
01:15 – What is an LLM (Large Language Model)?
04:03 – Transformer Architecture
08:43 – What is a Token and Tokenization?
12:50 – Tokenization and Context Window : Example
15:00 – Training vs Prompting
17:20 – Limitations of LLMs
22:03 – Next Steps

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🎯 Who Should Watch

• Software Developers
• AI Engineers
• Prompt Engineers
• Students Learning AI
• Tech Enthusiasts
• Product Managers

Join this channel to get access to perks:
https://www.youtube.com/channel/UCCTAmLlY-Fns7F16cOuVI7Q/join

🚀 Prompt Engineering For Developers Series

Episode 01 — Introduction to Prompt Engineering
Episode 02 — How LLMs Work
Episode 03 — Anatomy of a Good Prompt (Coming Next)

Playlist: https://www.youtube.com/playlist?list=PLt519PJr4jF9iDVju8UWE9LVtUqUFCR4f

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