Python for Data Science Essential Training Part 1

Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. It has now been updated and expanded to two parts—for even more hands-on experience with Python. In this course, instructor Lillian Pierson takes you step by step through a practical data science project: a web scraper that downloads and analyzes data from the web. Along the way, she introduces techniques to clean, reformat, transform, and describe raw data; generate visualizations; remove outliers; perform simple data analysis; and generate interactive graphs using the Plotly library. You should walk away from this training with basic coding experience that you can take to your organization and quickly apply to your own custom data science projects.

Topics include:

Why use Python for working with data
Filtering and selecting data
Concatenating and transforming data
Data visualization best practices
Visualizing data
Creating a plot
Creating statistical data graphics
Performing basic math and linear algebra
Correlation analysis
Multivariate analysis
Data sourcing via web scraping
Introduction to natural language processing
Collaborative analytics with Plotly