Link to the Platform: https://datagrad.netlify.app/
With the availability of numerous paid and free resources on the internet, it becomes overwhelming for students to learn new skills. DataGrad aims to bridge the gap between top MOOCs like Coursera, Udacity, EdX, and students eager to learn new skills. One only has to enter their level and the skill they want to learn, and DataGrad presents the Top 5 relevant courses carefully picked from various sites to them. The application will be beneficial for college students learning new skills, working professionals trying to upskill, and women on career breaks to revise concepts before re-joining.
The model takes the skill the user wants to learn and their level as input and presents the Top 5 relevant courses and medium articles to them as output.
A content-based recommender system built using the Python libraries - NumPy, Pandas, and strsim. The model works on the concept of cosine similarity between the skill input by the user and the database cleaned using Microsoft Excel and filtered based on the level of course/ article required. The modular approach makes it easier to deploy the model.
Built using HTML, CSS, ReactJS, and Bootstrap on the frontend and Flask on the backend, the website plays a significant role in the UI/UX experience. ParticleJS is used to add animations that are pleasing to the eye.
The Home Page of the Platform showcases DataGrad's Logo and is connected to the Explore, How to Use, Contact, and Team pages.
The How to Use Page presents a manual to use the Platform. The steps are given below:
The Explore Page has two options for Optimization. High Optimization refers to the skills related to which there are many courses in our database.
If the user opts for High Optimization, they have to select the skill they want to learn and their level from the select boxes. In case they have done any previous course related to the skill, they may enter that in order to get similar courses.
If the user opts not to go for High Optimization, they have to enter the skill they want to learn and select their level from the select box.
In either case, when the user selects/enters the options in the relevant fields, the courses are suggested as follows:
Behind every card, when the user clicks on the 'Check Out More' option, more courses offered by the University are displayed as follows. The user can toggle back using the 'Back to Course' option.
The Contact Page is for the users to write us their queries. We are still expanding our database, so if the courses recommended do not match one's expectations, we would really appreciate if they send us your query through the contact form and become a part of our family.
Data Wrangling:
Microsoft Excel
Data Manipulation:
Recommender System:
Front-End:
HTML CSS Bootstrap ReactJS ParticleJS
Back-End:
