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🎓 Smart Course Search

Smart Course Search is an intelligent search and recommendation system that helps users discover relevant courses based on semantic similarity rather than keyword matching. It is designed to improve course discoverability using NLP and machine learning techniques.

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📑 Table of Contents

• Overview
• App Preview
• Features
• Project Structure
• Tech Stack
• Setup
• Usage
• Dataset
• Hosting on GitHub
• Future Enhancements
• License

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🔍 Overview

Traditional keyword-based search often fails to capture user intent. Smart Course Search solves this by leveraging semantic understanding, enabling users to find the most relevant courses even when queries don’t exactly match course titles.

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🚀 App Preview (Smart Search LLM)

🔗 Live App Preview: 👉 https://ai.studio/apps/drive/1OZ6O_TCD3DJ6rLg2Ke_PStHaO_jhoFN2

This preview showcases the Smart Search LLM system in action, demonstrating:

• Semantic query understanding using Large Language Models
• Context-aware search results beyond keyword matching
• Intelligent ranking of retrieved results
• End-to-end search → retrieval → evaluation workflow

⚠️ Note: The app is hosted on AI Studio and may require sign-in access depending on permission settings.

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✨ Features

• 🔎 Semantic Course Search
• 📊 CSV-based Course Dataset
• 🧠 NLP-powered Similarity Matching
• ⚡ Fast and Lightweight
• 🛠 Easy to Extend and Customize

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📁 Project Structure

smart-course-search/
│── app.py                  # Main search application
│── data/
│   └── courses.csv         # Course dataset
│── requirements.txt        # Dependencies
│── README.md               # Documentation

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🛠 Tech Stack

• Language: Python

• Core Concepts: NLP, Semantic Search, Recommendation Systems

• Libraries:

  • pandas
  • scikit-learn / sentence-transformers (optional)
  • numpy

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⚙️ Setup

1. Clone the Repository

   git clone <your-github-repo-url>
   cd smart-course-search

2. Install Dependencies

   pip install -r requirements.txt

3. Load Dataset

   • Place your course data in:

     data/courses.csv
     

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▶️ Usage

Run the smart course search application:

python app.py

You can then enter a query (e.g., “machine learning for beginners”) and receive the most relevant course recommendations.

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📊 Dataset

The dataset should be a CSV file with fields such as:

course_id,course_title,description,category,level
1,Introduction to Machine Learning,Learn ML fundamentals...,AI,Beginner

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🌐 Hosting on GitHub

1. Initialize Git

   git init
   git add .
   git commit -m "Initial commit of smart course search system"

2. Push to GitHub

   git remote add origin <your-github-repo-url>
   git push -u origin main

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🚀 Future Enhancements

• Integrate LLM-based search (RAG)
• Add Streamlit / Web UI
• Support user feedback and ranking
• Deploy as a REST API
• Add vector databases (FAISS / Pinecone)

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📄 License

This project is licensed under the MIT License.

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