- Duration: 6h 32m 21s
- Skill Level: Beginner + Intermediate
- Released: April 10, 2017
- Viewers: 241,891
Learn the most in-demand business, tech and creative skills from industry experts.
Course detailsBy using Python to glean value from your raw data, you can simplify the often complex journey from data to value. In this practical, hands-on course, learn how to use Python for data preparation, data munging, data visualization, and predictive analytics. Instructor Lillian Pierson, P.E. covers the essential Python methods for preparing, cleaning, reformatting, and visualizing your data for use in analytics and data science. She helps to provide you with a working understanding of machine learning, as well as outlier analysis, cluster analysis, and network analysis. Plus, Lillian explains how to create web-based data visualizations with Plot.ly, and how to use Python to scrape the web and capture your own data sets.
Getting started with Jupyter
- [Instructor] Jupyter came with your Anaconda install, so let me show you how to run Jupyter. You just go to the application and launch it and then your console will open up. Right now, these are a bunch of files that I've been working with for the course, but let's look at some notebooks that come with the course. You're going to get all of these notebooks in the Exercises Files. Let's look at the first one. And I just wanted to point out that these are the cells where you code, and when you're coding you just want to make sure that they're set at code so that Jupyter knows to treat them that way. When you want to run the coding cell, you can either point and click this button here, or you could hit shift enter or control enter. That's the very basics about Jupyter and Notebook that you need for this course.
Practice while you learn with exercise filesDownload the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.Download the exercise files for this course. Get started with a free trial today.
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