https://github.com/ngangawairimu/data-visualization-with-python
Analyzed Coursera Course Dataset using Python for exploratory data analysis (EDA) and visualization to uncover insights on ratings, enrollments, and course attributes, providing actionable recommendations to optimize course offerings and enhance learner engagement.
https://github.com/ngangawairimu/data-visualization-with-python
barchart datavisualization matplotlib-python scatter-plot seaborn-plots
Last synced: 7 months ago
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Analyzed Coursera Course Dataset using Python for exploratory data analysis (EDA) and visualization to uncover insights on ratings, enrollments, and course attributes, providing actionable recommendations to optimize course offerings and enhance learner engagement.
- Host: GitHub
- URL: https://github.com/ngangawairimu/data-visualization-with-python
- Owner: ngangawairimu
- Created: 2024-11-22T07:22:14.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-12-11T15:12:13.000Z (10 months ago)
- Last Synced: 2025-01-28T14:52:49.923Z (8 months ago)
- Topics: barchart, datavisualization, matplotlib-python, scatter-plot, seaborn-plots
- Language: Jupyter Notebook
- Homepage:
- Size: 643 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
#### Download the data from Coursera Course Dataset.https://www.kaggle.com/siddharthm1698/coursera-course-dataset
## Project Overview
This project aims to analyze the Coursera Course Dataset, applying data visualization and exploratory data analysis (EDA) techniques learned in this and previous sprints. The dataset contains information on Coursera courses, including attributes such as course name, enrollment, ratings, Certificate level, and difficulty level. By performing EDA, we aim to extract actionable insights and identify patterns within the dataset.
### Insights
#### Course Ratings
- Most courses have high ratings, with most ratings clustering in the higher range, indicating positive feedback from learners.
#### Course Enrollment
- Courses with a "Mixed" difficulty level tend to have the highest average enrollments, followed by beginner-level courses. This suggests that courses designed for a broader range of learners attract more participants.
- The most-enrolled courses show significant interest, with a large variation in enrollments depending on the course topic.
#### Certificate Types
- Courses offering the "COURSE" certificate type tend to have the highest ratings compared to other certificate types like "SPECIALIZATION" and "PROFESSIONAL CERTIFICATE."
- Specialization courses may benefit from content enhancements to better match the high ratings seen in other types of courses.
#### Recommendations
Focus on Mixed-Level Courses
- Develop more "Mixed" difficulty courses, as these attract the most students. Consider creating courses that bridge foundational concepts with advanced applications.
Improve Specialization Courses
- Review and enhance the content of "Specialization" courses, focusing on learner feedback to improve ratings. Introduce practical projects or industry collaborations to make these courses more appealing.
Optimize Marketing for Beginner Courses
- Leverage marketing campaigns to promote Beginner-level courses, as they attract substantial enrollment. Highlight their accessibility and practical value for first-time learners.