Udemy Data Analysis Project

Project Overview

This project performs data analysis on Udemy course data, focusing on different course attributes like subjects, pricing, number of subscribers, and course levels. The goal is to explore key trends and insights from the available dataset.

Table of Contents

1. Data Loading and Preprocessing
2. Exploratory Data Analysis (EDA)
3. Data Visualization
4. Conclusion

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1. Data Loading and Preprocessing

In this step, we load the Udemy dataset and check for missing values to ensure the data is clean for further analysis.

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2. Exploratory Data Analysis (EDA)

In this section, we answer several key questions to gain insights into the dataset:

• What are the different subjects for which Udemy is offering courses?
• Which subject has the maximum number of courses?
• Which courses are free and which are paid?
• Top 5 most enrolled courses
• List courses related to Python
• What are the max number of subscribers per course level?

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3. Data Visualization

In this section, we create visualizations to better understand the data:

• Distribution of courses by subject
• Free vs Paid course distribution
• Top 5 most subscribed courses
• Enrollment by course level

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4. Conclusion

In this section, we summarize the findings from our analysis:

• Key insights from the distribution of courses, pricing, and subscribers
• Observations about the most popular subjects and course levels
• Understanding the free vs paid course distribution