Online Data Science Courses

All source code for Data Science Courses project on Kaggle platform including webcrawlers, preprocessing pipelines and EDA notebooks.

Demo

demo.mp4

Context

Nowadays, online educational platforms provide a vast amount of online courses. For self-learning beginners in Data Science, sometimes it's hard to choose an online course to start. This data was collected with the intent to answer common questions when choosing a new study.

Acknowledgements

Data was collected via web scraping from popular online platforms: Coursera, Stepik, Udemy, edX, Pluralsight, Alison, FutureLearn, and Skillshare. From each platform were queried courses only related to the "Data Science" topic. The original author of the image thumbnail is Ales Nesetril.

Inspiration

The primary intent behind collecting courses data is to discover which online platform provides the highest educational quality. Also, further analysis should reveal answers like "Does a paid course provide higher quality than a free one?" or "Which platform is the most suitable for beginners?".

Structure

• Web crawlers
  • Scrapy crawlers
  • Selenium crawlers
• On-demand dataframe
• EDA notebooks
• Data processing pipelines
• Test suites
• Common utility scripts

Getting started

Before setting up the environment, ensure you have Make installed on your local machine. To install the packages required for the Streamlit dashboard, use the following command:

make min-dep

If you prefer a virtual environment setup, use requirements.txt. You can set up extra dependencies for development, testing, data collection, and processing with the command:

make all-dep

To run a Streamlit server, use the command:

make serve