[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-81173":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":8,"htmlUrl":8,"language":9,"languages":8,"totalLinesOfCode":8,"stars":10,"forks":11,"watchers":10,"openIssues":12,"contributorsCount":12,"subscribersCount":12,"size":12,"stars1d":12,"stars7d":12,"stars30d":12,"stars90d":12,"forks30d":12,"starsTrendScore":12,"compositeScore":13,"rankGlobal":8,"rankLanguage":8,"license":14,"archived":15,"fork":15,"defaultBranch":16,"hasWiki":17,"hasPages":15,"topics":18,"createdAt":8,"pushedAt":8,"updatedAt":19,"readmeContent":20,"aiSummary":21,"trendingCount":12,"starSnapshotCount":12,"syncStatus":22,"lastSyncTime":23,"discoverSource":24},81173,"intelligence-career-guidance","JAMES-2225\u002Fintelligence-career-guidance","JAMES-2225",null,"JavaScript",28,1,0,37.9,"MIT License",false,"main",true,[],"2026-06-13 04:01:28","# 🧠 CareerIQ — Intelligent Career Guidance & Skill Recommendation Platform\n\n![Python](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPython-3.10+-3776AB?style=flat&logo=python&logoColor=white)\n![Flask](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FFlask-3.0-000000?style=flat&logo=flask&logoColor=white)\n![React](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FReact-18-61DAFB?style=flat&logo=react&logoColor=black)\n![Pandas](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPandas-2.x-150458?style=flat&logo=pandas&logoColor=white)\n![License](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FLicense-MIT-green?style=flat)\n\n> IT4609 — Mini Project | St. Joseph's Institute of Technology, Chennai\n\nAn intelligent, data-driven platform that provides **personalized career recommendations**, performs **skill gap analysis**, and suggests **online courses** to bridge those gaps — all in one unified system.\n\n---\n\n## 📑 Table of Contents\n\n- [Overview](#overview)\n- [Features](#features)\n- [Tech Stack](#tech-stack)\n- [Project Structure](#project-structure)\n- [Getting Started](#getting-started)\n  - [Backend Setup](#backend-setup)\n  - [Frontend Setup](#frontend-setup)\n- [API Reference](#api-reference)\n- [Supported Career Domains](#supported-career-domains)\n- [Future Enhancements](#future-enhancements)\n- [Contributors](#contributors)\n\n---\n\n## Overview\n\nStudents today struggle to choose the right career path due to rapidly changing industry requirements and the sheer number of options available. **CareerIQ** solves this by:\n\n1. **Collecting** the user's current skills and areas of interest.\n2. **Matching** the profile against a curated career dataset using intelligent similarity scoring.\n3. **Identifying skill gaps** — skills required for the top career matches that the user doesn't yet have.\n4. **Recommending courses** from platforms like Coursera, Udemy, and freeCodeCamp to bridge those gaps.\n\n---\n\n## Features\n\n| Feature | Description |\n|---|---|\n| 🎯 Career Recommendation | Top-3 career matches ranked by match percentage |\n| ⚡ Skill Gap Analysis | Identifies missing skills for each recommended career |\n| 📚 Course Recommendations | Curated online courses per missing skill |\n| 🗺️ Explore Careers | Browse all 20 career paths across 6 domains |\n| 💰 Salary & Demand Info | Average salary and job demand indicator per career |\n| 📱 Responsive UI | Works on desktop and mobile browsers |\n\n---\n\n## Tech Stack\n\n### Backend\n- **Python 3.10+**\n- **Flask** — REST API framework\n- **Flask-CORS** — Cross-origin support\n- **Pandas \u002F NumPy** — Data processing and recommendation logic\n- **CSV-based dataset** — Career and course data\n\n### Frontend\n- **React 18** — Component-based UI\n- **Axios** — HTTP client\n- **CSS (custom)** — Inter font, responsive grid layout\n\n---\n\n## Project Structure\n\n```\nintelligence-career-guidance\u002F\n├── backend\u002F\n│   ├── app.py                   # Flask API (recommendation engine)\n│   ├── requirements.txt         # Python dependencies\n│   ├── career_dataset.csv       # 20 career profiles with skills & salary data\n│   └── skill_courses_dataset.csv# 33 courses mapped to skills & platforms\n│\n├── frontend\u002F\n│   ├── public\u002F\n│   │   └── index.html\n│   ├── src\u002F\n│   │   ├── App.js               # Root component, routing between tabs\n│   │   ├── index.js\n│   │   ├── components\u002F\n│   │   │   ├── Header.js\n│   │   │   ├── Footer.js\n│   │   │   ├── CareerForm.js    # Skills & interest input form\n│   │   │   ├── RecommendationResults.js  # Top-3 results cards\n│   │   │   ├── SkillGapCard.js  # Missing skills display\n│   │   │   ├── CourseCard.js    # Individual course tile\n│   │   │   └── ExploreCareersList.js     # Browse all careers\n│   │   └── styles\u002F\n│   │       ├── index.css\n│   │       └── App.css\n│   └── package.json\n│\n├── docs\u002F\n│   └── architecture.md\n│\n├── .gitignore\n├── LICENSE\n└── README.md\n```\n\n---\n\n## Getting Started\n\n### Prerequisites\n\n- Python 3.10+\n- Node.js 18+ and npm\n\n### Backend Setup\n\n```bash\n# 1. Navigate to the backend folder\ncd backend\n\n# 2. Create a virtual environment (recommended)\npython -m venv venv\n\n# On Windows:\nvenv\\Scripts\\activate\n# On macOS\u002FLinux:\nsource venv\u002Fbin\u002Factivate\n\n# 3. Install dependencies\npip install -r requirements.txt\n\n# 4. Start the Flask server\npython app.py\n```\n\nThe backend will start at **http:\u002F\u002F127.0.0.1:5000**\n\n### Frontend Setup\n\n```bash\n# 1. Navigate to the frontend folder (in a new terminal)\ncd frontend\n\n# 2. Install npm packages\nnpm install\n\n# 3. Start the development server\nnpm start\n```\n\nThe React app will open at **http:\u002F\u002Flocalhost:3000**\n\n> **Note:** Make sure the Flask backend is running before starting the frontend, otherwise the API calls will fail.\n\n---\n\n## API Reference\n\nAll endpoints return JSON.\n\n### `GET \u002F`\nHealth check.\n\n**Response:**\n```json\n{ \"status\": \"Career Guidance API is running\", \"version\": \"1.0.0\" }\n```\n\n---\n\n### `POST \u002Frecommend`\nGet personalized career recommendations.\n\n**Request Body:**\n```json\n{\n  \"skills\": \"Python Machine Learning SQL\",\n  \"interest\": \"Data Science\"\n}\n```\n\n**Response:**\n```json\n{\n  \"user_skills\": [\"Python\", \"Machine Learning\", \"SQL\"],\n  \"user_interest\": \"Data Science\",\n  \"recommendations\": [\n    {\n      \"career\": \"Data Scientist\",\n      \"domain\": \"Data Science\",\n      \"description\": \"...\",\n      \"avg_salary\": 95000,\n      \"job_demand\": \"Very High\",\n      \"match_percentage\": 75.0,\n      \"skill_gap\": [\"Statistics\", \"Data Visualization\", \"NumPy\"],\n      \"recommended_courses\": [ ... ]\n    }\n  ]\n}\n```\n\n---\n\n### `POST \u002Fskill-gap`\nAnalyse skill gap for a specific career.\n\n**Request Body:**\n```json\n{\n  \"skills\": \"Python SQL\",\n  \"career\": \"Data Scientist\"\n}\n```\n\n---\n\n### `GET \u002Fcareers`\nList all careers and domains.\n\n---\n\n### `GET \u002Fcourses?skill=Python`\nList courses filtered by skill (optional query param).\n\n---\n\n## Supported Career Domains\n\n| Domain | Careers |\n|---|---|\n| 📊 Data Science | Data Scientist, Data Analyst, Database Administrator |\n| 🤖 Artificial Intelligence | ML Engineer, AI Research Scientist, NLP Engineer |\n| 🌐 Web Development | Frontend, Backend, Full Stack Developer, UI\u002FUX Designer |\n| ☁️ Cloud Computing | Cloud Engineer, DevOps Engineer, Cloud Architect |\n| 🔒 Cyber Security | Security Analyst, Penetration Tester, Security Engineer |\n| 💻 Software Development | Software Developer, Mobile Developer, Embedded Systems, Blockchain |\n\n---\n\n## Future Enhancements\n\n- 🤖 Advanced ML models (Random Forest, Neural Networks) for better matching\n- 🗣️ NLP-based resume parsing and analysis\n- 🌍 Real-time job market API integration (LinkedIn, Indeed)\n- 💬 AI chatbot for conversational career guidance\n- 🌐 Multilingual support\n- 📱 Mobile application (Flutter \u002F React Native)\n- 👤 User accounts and recommendation history (MySQL)\n- 📊 Personality assessment integration\n\n---\n\n## Contributors\n\n| Name | Roll Number |\n\n| Panimaya James R | 312423205158 |\n\n**Supervisor:** Mrs. P. Saranya M.E (Ph.D), Assistant Professor  \n**Department:** Information Technology  \n**Institution:** St. Joseph's Institute of Technology, Chennai — 600 119\n\n---\n\n## License\n\nThis project is licensed under the [MIT License](LICENSE).\n","CareerIQ 是一个智能职业指导与技能推荐平台，旨在帮助用户根据个人技能和兴趣获得定制化的职业发展建议。其核心功能包括提供个性化职业推荐、进行技能差距分析以及推荐在线课程以弥补这些差距。技术上，该项目采用了Python 3.10+和Flask构建后端服务，使用Pandas处理数据；前端则基于React 18开发，确保了良好的用户体验。适用于学生或职业初期者探索适合自己的职业道路，或是希望在现有领域内提升技能的专业人士。",2,"2026-06-11 04:03:46","CREATED_QUERY"]