Python for Data Science Essential Training Part 1

English | 6h 2m | Video 720p | Subtitles | Project File

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

 

Homepage:

https://www.lynda.com/Python-tutorials/Python-Data-Science-Essential-Training-Part-1/5025803-2.html