Скачать или смотреть 🧠 LLM Logic Explained — IIT Madras BS Project 1 (Tools in Data Science)

🎓 IIT Madras BS in Data Science and Programming
📘 Course: Tools in Data Science
🧩 Project 1: LLM Code Deployment – LLM Logic Explained

In this focused video, I explain only the LLM component of Project 1 – LLM Code Deployment from the IIT Madras BS Tools in Data Science course.

You’ll learn how the Large Language Model (LLM) interacts with your code, APIs, and repository — and how it fits into the Build → Evaluate → Revise workflow of the project.

🔍 What You’ll Learn

✅ How the LLM interprets JSON requests
✅ Structure of the input and output JSON
✅ Validating the secret key before calling the LLM
✅ How the LLM generates app code automatically
✅ Understanding how the system triggers deployment
✅ Role of the evaluation API and LLM feedback in Round 2
✅ Common mistakes students make in LLM response handling

🧠 LLM Project Flow Summary

1️⃣ Build Phase:
Receive JSON → Verify secret → Use LLM to create app → Deploy to GitHub Pages

2️⃣ Evaluate Phase:
Instructor system checks repo structure, code quality, and LLM-generated outputs

3️⃣ Revise Phase:
Receive second JSON → Update via LLM → Re-deploy → Submit for re-evaluation

⚙️ Technologies Involved

Large Language Models (LLMs)

JSON API Integration

GitHub API / Pages

HTTP Request & Response Handling

Automated Evaluation System

💡 Resources


🔗 GitHub Pages Setup: https://pages.github.com/

🔗 LLM Prompting Tips for Coding (coming soon)

🎯 Who Should Watch

IITM BS students doing Tools in Data Science – Project 1

Learners exploring how LLMs can automate app development and deployment

Anyone wanting a clear breakdown of LLM → Code → Deploy logic

📬 Connect

💬 Have questions? Drop them in the comments — I’ll try to guide you!


📢 Disclaimer: This is an **independent educational video**, not an official IITM communication.