Project Overview AI Career Boost is a platform designed to help students build strong portfolios and find suitable universities for admission. It enables users to create portfolios without the need for external mentors, helping them save money during the admission process.
Target Audience Young people who want to create a competitive portfolio. Students seeking the best educational institutions without professional guidance. Technological Stack Frontend: React.js – Provides an intuitive interface for users to input data and view analyses. Backend: Node.js – Handles data processing and database interaction. Database: MongoDB – Stores user portfolios and other related data. Data Scraping & Analysis: Python – Extracts and analyzes opportunities (e.g., contests, events). AI Model: Gemini – Processes text for generating recommendations and insights. AI Functionality Portfolio Analysis: AI identifies strengths and weaknesses in the user's portfolio and provides recommendations for improvement. University Recommendations: AI suggests nine universities categorized as: 3 Target Universities – Moderate match. 3 Match Universities – Strong match. 3 Reach Universities – More ambitious options. Statistics & Analytics Python collects and processes data related to extracurricular opportunities. Data is visualized using graphs for better user comprehension. Workflow The user inputs portfolio data. A Python script scrapes relevant opportunities. The backend (Node.js) stores and processes data in MongoDB. AI (Gemini) analyzes the data and provides recommendations. Users receive personalized insights and university suggestions. Areas for Improvement Expanding the scraping catalog to include more local and international sources. Enhancing university selection and adding a feature for essay topic recommendations. Improving frontend design for a more user-friendly experience.
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