Educative Course Analysis

In this project, I will be analyzing various Educative courses categorized under 4 distinct subjects : Web development, Business Finance, Musical Instruments and Graphic design. The goal of the analysis is to assess the performance (both financially and otherwise) of the various courses over the 7 year period (2011–2017) and explore opportunities for growth. To help me do this, I will use Microsoft Excel and Power BI to facilitate the transformation and visualization of the data.

Data Source & Design

The data for this project was sourced from Educative for educational purposes. Educative is a massive online open course (MOOC) platform that offers both free and paid courses with a focus on tech courses. This dataset contains 3676 records of courses from 4 subjects (Business Finance, Graphic Design, Musical Instruments and Web Development) taken from Educative.

Data Structure

• course_id — Course ID
  • course_title — Course Title
  • subject — subject under which course is
  • url — Course URL
  • publish_date — day of week , full date on which course was published
  • publish_time — time of day course was published
  • price — Course Price
  • num_subscribers — Number of subscribers
  • revenue — revenue course generated
  • num_reviews — Number of reviews
  • num_lectures — Number of lectures
  • level — Course difficulty
  • rating — rating of course
  • content_duration — Duration of all course materials

Data Cleaning

• Duplicates within the data set were removed.
• Blank cells were removed
• Subject titles were formatted to be consistent throughout the data

Data Transformation

• Date Timestamp was split into 2 columns, creating a date column and a time column.
• Pivot tables were created in Excel to summarize data and expedite chart creation.
• Bins were created for specific data to facilitate analysis

Created columns

• Price Band : {free : 0 ; low : less than $50 ; medium : between $50 and $130 ; high : above $130}
• Free_or_paid : {free : $0 ; paid: not $0}
• Rate_band : {low : less than 0.4 ; mid : from 0.4(inclusive) to 0.7; high : 0.7 or higher}

Visualizations

Pie Chart: Used where a quick glance at proportions answered the question at hand.

Stacked Column Chart: Used where whole measures broken down by categories needed to be shown.

Clustered Column Chart: Used where the differences in categories within a measure needed to be shown.

Clustered Bar Chart: Used where the differences in categories within a measure needed to be shown.

Table: Used where a capture of key measures limited by filters were needed.

Area Chart: Used where progression over time needed to be shown

Findings

• Web development consistently had the most subscribers over the period despite Educative having published about as many courses in Business finance. It appears most of our subscribers come to us for tech courses which aligns with our mission.

Proportion of Subscribers Over 7 years

Number of Courses per Subject

• Average price of a web development course is relatively high regardless of difficulty level. Subscribers were willing to pay more for these courses.

Average Price of Subjects over 7 years

• Graphic design courses received the highest ratings regardless of difficulty level especially the Expert level courses though said courses cost the least on average.

Average Rating per Subject by Levels

• Far more people subscribed to paid courses than to free courses.

Subscriber Count by Subject per payment

• Interestingly, within our top 20 courses pulling the most subscribers, we saw 2 free subscribers for every paid subscriber, with the highest ranking course being a free course.

• Far more subscribers purchased web development courses that were highly priced than lowly priced.

• Subscribers appeared to be gravitating towards beginner level courses with the advent of many tech job opportunities.

• Few courses have been categorized as Expert Level.

Conclusion

• Educative can look at publishing more Graphic design courses and charging higher for the Expert Level Graphic Design courses as they received the highest ratings on average.
• Educative can look at charging a pittance (to test the waters) for highly rated and popular (highly subscribed) courses that are currently free.
• Web development courses that are in the low price band may be increased to the medium price band as we have seen that subscribers are filling to pay more for worth-while courses.
• We can revise the quality of lowly rated web development courses. These courses are currently pulling substantial revenue, however, improving the quality of these courses will attract even more subscribers and consequently revenue.
• In the near future, we can invest in Expert Level courses as many of our users who took beginner and intermediate level courses will require expert level courses to upskill.

Thank you for taking the time to to look through this project, I hope it helped you along your analytics journey. You can see more projects from me here , visit my Github for the full dataset. and see some dashboards here. Let’s connect on LinkedIn.