/STA_Project

Exploring Online Learning Landscapes: Insights and Recommendations from Course Data Analysis

Primary LanguageHTML

STA 220 Project (Winter 2024)

Exploring Online Learning Landscapes: Insights and Recommendations from Course Data Analysis

Code Structure

  • Within the directories Coursera, Udemy, and PluralSight, you'll find the .ipynb files responsible for data scraping or fetching data using APIs from their respective sites. Additionally, each directory contains a file named <course_platform>_course_all_info.csv, which comprehensively stores all data pertaining to the columns indicated below.

  • The file named Data Merger.ipynb houses the code necessary for merging data acquired from all sources. The merged dataset is then saved into a file titled all_courses_data.csv.

  • Within the Course Recommendation.ipynb file, you'll discover code designed to recommend courses based on cosine similarity. This includes preprocessing steps, the recommendation algorithm, and the recommendation function.

  • The contents of the Visualization/Visualization.ipynb file pertain to data visualization. All resulting *.html files are generated as a consequence of these visualizations.

Table Columns Fetched

  1. course_id (ud:udemy, ce:coursera, ps: PluralSight)
  2. course_title
  3. course_url
  4. course_instructor
  5. course_rating (out of 5)
  6. course_duration (In hrs)
  7. course_details (Definition based on the source)
  • Udemy(Description+ What you'll learn)
  • Courseera(Skills you'll gain + Modules Description)
  • PluralSight(What you'll learn)
  1. course_level (All: 0, Beginner: 1, Intermediate: 2, Advanced: 3)
  2. course_no_of_reviews
  3. course_no_of_enrolled