Udemy Course Engagement and Pricing Data

Columns

• id: The unique identifier associated with the specific course.
• title: The name or title of the course (e.g., 'WordPress for Beginners').
• url: The direct URL path to the course on the Udemy website.
• is_paid: A boolean indicator (True/False) specifying whether the course requires payment or is free.
• num_subscribers: The total count of students subscribed to the course.
• avg_rating: The average user rating score for the course on a scale of 0 to 5.
• avg_rating_recent: A metric reflecting recent changes in the average rating.
• rating: The general course rating value.
• num_reviews: The total number of written reviews or ratings the course has received.
• is_wishlisted: A boolean value indicating if the course is in user wishlists (predominantly False in this sample).
• num_published_lectures: The total number of lectures available within the course content.
• num_published_practice_tests: The quantity of practice tests provided by the course.
• created: The timestamp recording when the course was originally created (ranging from 2010 to 2020).
• published_time: The timestamp recording when the course was officially published.
• discount_price__amount: The value of the course price after discounts have been applied.
• discount_price__currency: The currency code for the discounted price (primarily INR).
• discount_price__price_string: The formatted string displaying the discounted price (e.g., ₹490).
• price_detail__amount: The original, non-discounted price value of the course.
• price_detail__currency: The currency code for the original price.
• price_detail__price_string: The formatted string displaying the original price.

Distribution

• Format: CSV (Comma Separated Values)
• Size: Approximately 8.79 MB
• Structure: 20 columns per record
• Rows: 39,700+ valid records (Total count listed as roughly 39k courses)
• Data Integrity: High validity across key fields (100% valid for IDs, Titles, and URLs; 0% missing values for primary metrics).

Usage

• Market Analysis: Evaluate the demand for specific lifestyle skills by analysing subscriber counts and review volumes.
• Pricing Strategy: Investigate the relationship between course length (number of lectures), pricing (original vs. discounted), and subscriber acquisition.
• Trend Forecasting: Identify emerging topics in the lifestyle sector by tracking course creation and publication dates over time.
• Sentiment Analysis: Assess learner satisfaction through average ratings and recent rating changes.
• Content Optimisation: Determine the optimal number of lectures or practice tests associated with highly-rated courses.

Coverage

• Time Range: The dataset covers course creation and publication dates spanning from August 2010 to October 2020.
• Geographic/Currency Scope: Pricing data is primarily denominated in INR (Indian Rupee), suggesting a regional pricing focus or extraction context, though the content is global.
• Subject Matter: Focuses on the 'LifeStyle' category, including sub-domains like Pet Care, Gaming, Travel, and Beauty.
• Demographic Target: Includes tags for various skill levels such as 'Beginner'.

License

Who Can Use It

• E-learning Platforms: For benchmarking content catalogues and pricing models against a major competitor.
• Educational Researchers: To study the growth of non-formal online education in lifestyle and hobby sectors.
• Data Analysts: For practising data cleaning, visualisation, and exploratory data analysis (EDA).
• Content Creators: To identify under-served niches or highly popular topics within the lifestyle domain.

Dataset Name Suggestions

• Udemy Lifestyle Course Metrics 2010-2020
• Global E-Learning Trends: Lifestyle Category
• Udemy Course Engagement and Pricing Data
• Lifestyle Education Market Analysis Set

Attributes