CoolFace
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aman-secret/online-courses-usage-and-history-dataset

Online Courses Dataset This repository provides a comprehensive dataset of online courses, including details about course categories, duration, platforms, enrollment numbers, completion rates, and ratings. The dataset can be used for trend analysis, platform comparisons, and market insights. Key Features Course Categories: Analyze trends across AI, Business, Data Science, Design, Finance, and more. Enrollment Metrics: Understand popularity with student… See the full description on the dataset page: https://huggingface.co/datasets/aman-secret/online-courses-usage-and-history-dataset.

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Dataset Card

Online Courses Dataset

This repository provides a comprehensive dataset of online courses, including details about course categories, duration, platforms, enrollment numbers, completion rates, and ratings. The dataset can be used for trend analysis, platform comparisons, and market insights.

Key Features

  • —Course Categories: Analyze trends across AI, Business, Data Science, Design, Finance, and more.
  • —Enrollment Metrics: Understand popularity with student enrollment numbers.
  • —Completion Rates: Assess student engagement with course completion rates.
  • —Platform Analysis: Compare offerings from Coursera, edX, Udemy, and others.
  • —Pricing and Ratings: Evaluate courses based on price and user feedback.

Visual Insights

1. Enrolled Students by Category

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2. Average Completion Rate by Platform

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3. Price vs Rating

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4. Top Platforms by Enrolled Students

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5. Completion Rates Among Categories

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Installation

To use the dataset and its visualizations, follow the steps below:

Prerequisites

  • —Python 3.7 or higher
  • —Libraries: pandas, matplotlib, seaborn

Installation Steps

  1. 1.Clone the Repository:
bash
   git clone https://github.com/yourusername/online-courses-dataset.git
   cd online-courses-dataset
  1. 1.Install Required Libraries:
bash
   pip install -r requirements.txt
  1. 1.View the Dataset:

Open and explore online_courses_uses.csv using your preferred tool or script.

  1. 1.Generate Visualizations:

Run the provided visualize.py script to generate charts and insights:

bash
   python visualize.py

Reference

For additional details and dataset card metadata, see Hugging Face Dataset Card Template.

Contributing

Contributions are welcome! Please fork the repository, make your changes, and submit a pull request. Ensure your code is well-documented and adheres to the repository standards.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For inquiries or collaborations, contact us at sfait.pro@gmail.com.