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Global Online Data Science Course Catalogue
Education & Learning Analytics
Tags and Keywords
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"No reviews yet"
Free
About
Curated from multiple major online educational providers, this collection aggregates information on Data Science courses to assist self-learners and analysts in navigating the e-learning landscape. By centralizing data from platforms such as Coursera, Udemy, and edX, the file enables the analysis of educational quality, course popularity, and value propositions across the market. The records address common questions regarding course selection, allowing users to investigate relationships between course duration, difficulty levels, user ratings, and pricing models to determine the most suitable learning pathways.
Columns
- Course ID: Unique identifier for the course record.
- title: The specific name or title of the online course.
- author: The instructor, university, or organisation providing the course (e.g., Coursera Project Network, Packt Publishing).
- rating: User-generated rating on a scale of 0 to 5.
- votes_count: The number of reviewers who have rated the course.
- students_count: The total number of participants enrolled in the course.
- level: The difficulty or required skill level for the course (e.g., Beginner, Mixed).
- duration: Approximate length of the course in hours.
- platform: The online distribution provider hosting the course (e.g., Udemy, Skillshare).
- free: A boolean indicator specifying whether the course is free or paid.
Distribution
The data is structured in a single tabular CSV file named
dataframe.csv. It contains approximately 4,683 records and 10 columns, with a file size of roughly 523.14 kB.Usage
- Market Analysis: Evaluating which platforms dominate the Data Science education sector.
- Price-Quality Comparison: Investigating whether paid courses consistently offer higher ratings than free alternatives.
- Recommender Systems: Building tools to suggest courses to beginners based on popularity and difficulty level.
- Trend Analysis: Identifying the most common providers and course durations preferred by students.
Coverage
The data covers Data Science curricula available on the internet via major global e-learning platforms including Coursera, Stepik, Udemy, edX, Pluralsight, Alison, FutureLearn, and Skillshare. It focuses specifically on the "Data Science" topic domain.
License
CC0: Public Domain
Who Can Use It
- Self-learners: Individuals seeking to identify the highest-rated or most popular courses for their skill level.
- EdTech Analysts: Researchers studying trends in online education and platform market share.
- Content Creators: Instructors benchmarking their content against market leaders.
- Data Science Students: Beginners practising exploratory data analysis on a clean, real-world dataset.
Dataset Name Suggestions
- Global Online Data Science Course Catalogue
- E-Learning Platform Metrics for Data Science
- Aggregated Data Science Course Ratings and Stats
- Multi-Platform MOOC Directory
Attributes
Original Data Source: Global Online Data Science Course Catalogue
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