Wienext Project Wienext is a personalized skill-learning platform that leverages AI-driven recommendations, providing users with tailored learning roadmaps, video recommendations, and an intuitive onboarding experience. The platform integrates advanced machine learning models, YouTube video recommendations, and user-friendly interfaces.

Directory Structure plaintext Copy code wienext/ ├── roadmaps/ │ ├── static/ │ │ ├── css/ │ │ │ └── roadmap.css # CSS for roadmap pages │ │ └── js/ │ │ └── roadmap.js # JavaScript for roadmap interactivity │ ├── templates/ │ │ ├── roadmap_detail.html # Template for detailed roadmap view │ │ └── roadmap_list.html # Template for listing available roadmaps │ ├── init.py # Package initialization │ ├── models.py # Database models for roadmaps │ ├── urls.py # URL routing for roadmap views │ └── views.py # Views for handling roadmap requests ├── skill_learning/ │ ├── api/ │ │ ├── urls.py # API endpoint definitions │ │ └── views.py # API views for handling requests │ ├── models/ │ │ ├── ncf_recommendation.py # Neural Collaborative Filtering model │ │ └── tfidf_recommendation.py # TF-IDF recommendation model │ ├── utils/ │ │ ├── data_preprocessing.py # Functions for cleaning and preparing data │ │ └── model_helpers.py # Helper functions for model training and evaluation │ ├── youtube_recommendation.py # YouTube video recommendation logic │ └── video_recommendation.py # Generic video recommendation handling ├── users/ │ ├── static/ │ │ ├── css/ │ │ │ └── style.css # CSS for user dashboard and onboarding │ │ └── js/ │ │ └── script.js # JavaScript for user interactions │ ├── templates/ │ │ ├── dashboard.html # User dashboard template │ │ ├── onboarding.html # Onboarding process template │ │ └── roadmap_list.html # Roadmap listing template for users │ ├── init.py # Package initialization │ ├── ai_onboarding.py # AI logic for onboarding personalization │ ├── forms.py # Django forms for user input │ ├── models.py # User-related database models │ ├── urls.py # URL routing for user views │ └── views.py # Views for handling user requests ├── templates/ │ ├── base.html # Base template for common layout │ └── common_layout.html # Common layout template for the site ├── db.sqlite3 # SQLite database file ├── Dockerfile # Docker configuration for containerization ├── manage.py # Django's command-line utility ├── README.md # Project documentation ├── requirements.txt # Python dependencies for the project └── tests.py # Test cases for the application Code Description roadmaps/ Static Files: Contains CSS and JS specific to the roadmap features. Templates: HTML files for displaying roadmaps and details. Models: Defines the structure of the roadmap data. Views: Handles requests related to roadmaps, such as viewing and listing roadmaps. skill_learning/ API: Defines RESTful endpoints for interacting with the recommendation system. Models: Contains the recommendation models (NCF and TF-IDF) used for suggesting skills and resources. Utils: Functions for data preprocessing and model assistance. YouTube Recommendation: Logic to fetch and recommend YouTube videos based on user preferences. Video Recommendation: General logic for handling video recommendations. users/ Static Files: CSS and JS for user-facing pages like the dashboard and onboarding. Templates: HTML files for user interactions, including onboarding and dashboards. AI Onboarding: Implements AI-driven personalization for new users. Forms: Handles user input forms. Models: Defines user-related data structures. Views: Manages user requests and interactions. templates/ Base Templates: Common layout files to maintain consistency across the site. db.sqlite3 SQLite database storing application data. Dockerfile Configuration for containerizing the application using Docker. manage.py Django’s command-line utility for project management. requirements.txt Lists all Python dependencies required for the project. tests.py Contains unit tests to ensure the integrity of the application. Setup Instructions Clone the Repository:

bash Copy code git clone https://github.com/your-repo/wienext.git cd wienext Install Dependencies: Ensure Python 3.8+ and pip are installed. Then run:

bash Copy code pip install -r requirements.txt Database Setup: Run migrations to set up the database schema:

bash Copy code python manage.py makemigrations python manage.py migrate Run the Server: Start the Django development server:

bash Copy code python manage.py runserver Access the Application: Open a browser and navigate to http://localhost:8000.

Team Member Deliverables Backend Developers Enhance API Functionality: Implement additional endpoints in skill_learning/api/views.py. Model Optimization: Improve performance of the NCF and TF-IDF models in skill_learning/models/. AI Onboarding: Refine the onboarding logic in users/ai_onboarding.py to better personalize user experiences. Frontend Developers UI Enhancements: Update users/templates/dashboard.html and onboarding.html for a more intuitive interface. Interactive Features: Enhance user interactivity through users/static/js/script.js. Data Scientists Model Development: Explore additional recommendation models and integrate them into skill_learning/models/. Data Preprocessing: Enhance skill_learning/utils/data_preprocessing.py for more robust data handling. Project Managers Documentation: Ensure all code is well-documented, and maintain an updated README.md. Testing: Oversee the creation and execution of test cases in tests.py. Contributing Contributions are welcome! Please fork the repository, make your changes, and submit a pull request.

License This project is licensed under the MIT License.