Bite-Sized Data Science with Python: Introduction
WEBRip | MP4/AVC, ~664 kb/s | 1280 x 720 | English: AAC, 58.5 kb/s (2 ch), 48.0 KHz | 418 MB
Genre: Development / Programming Languages | Language: English | +Project Files
"Follow along as we analyze a real-life dataset and learn data science with Python"
Learn the basics of data science with Python, with this short course designed for students to follow along, and built around a concrete, real-world dataset.
Listening to theoretical examples is never fun, and I've always liked actually applying what I learn to concrete examples, so this course is built around us analyzing a real-life dataset together. The dataset we'll be using is the "Parkinson's Disease Telemedicine dataset", and our goal will be to see if we can predict the severity of Parkinson's Disease in patients from just a dozen simple measurements, which would be a vast improvement over the current time consuming process that doctors and patients have to go through.
This course will provide a good introduction to several different aspects of data science, and all in Python, one of the most popular and powerful languages used by data scientists today.
You'll learn how to:
- Set up your data analysis research environment (in an iPython notebook)
- Visualize the data to understand it better
- Manipulate and transform data to prepare it for modeling
- Apply a statistical model to the data
The course is comprised of short lectures which walk you through the data analysis, as you follow along. There are also several coding exercises throughout to test your knowledge!
Check out the course to learn data science with Python today!
What are the requirements?
Students should have experience writing, at a minimum, basic programs in Python
What am I going to get from this course?
Over 24 lectures and 1 hour of content!
Manipulate and transform data series and tables in Python
Build a multiple regression model in Python
Use iPython Notebook for research and analysis in Python
Visualize data to glean insights from it, in Python