Python Statistics Essential Training

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Matt Harrison

2:39:25

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01 - Introduction

01 - Being a Python statistics MVP.mp4

00:50

02 - What you should know.mp4

00:41

03 - Using GitHub Codespaces with this course.mp4

03:06

02 - 1. Loading and Cleaning Data

01 - Loading data.mp4

05:28

02 - Strings and categories.mp4

15:59

03 - Cleaning numbers.mp4

15:57

04 - Shrinking numbers.mp4

05:50

05 - Challenge Clean Ames.mp4

01:37

06 - Solution Clean Ames.mp4

04:23

03 - 2. Exploring and Visualizing

01 - Categorical exploration.mp4

04:02

02 - Histograms and distributions.mp4

04:22

03 - Outliers and Z-scores.mp4

06:52

04 - Correlations.mp4

07:02

05 - Scatter plots.mp4

07:37

06 - Visualizing categorical and numerical values.mp4

10:42

07 - Comparing two categoricals.mp4

06:02

08 - Challenge Explore Ames.mp4

00:27

09 - Solution Explore Ames.mp4

03:28

04 - 3. Linear Regressions

01 - Linear regression.mp4

07:21

02 - Interpreting linear regression models.mp4

04:20

03 - Standardizing values.mp4

06:22

04 - Regression with XGBoost.mp4

08:42

05 - Challenge Predict Ames.mp4

00:40

06 - Solution Predict Ames.mp4

03:55

05 - 4. Hypothesis Tests

01 - Exploring data.mp4

02:40

02 - Visualizing distributions.mp4

06:03

03 - Running statistical tests.mp4

04:24

04 - Testing for normality.mp4

04:28

05 - Challenge Checking square footage distributions.mp4

00:20

06 - Solution Checking square footage distributions.mp4

04:27

06 - Conclusion

01 - Next steps.mp4

01:18

Description

The field of statistics has become increasingly dependent on data analysis and interpretation using Python. With the rise of big data and data science, the demand for professionals who can effectively analyze and interpret data using Python has skyrocketed. In this course, Matt Harrison teaches you how to collect, clean, analyze, and visualize data using the powerful tools of the Python programming language. Join Matt as he gives into the various techniques that form the backbone of statistics and helps you understand the data with summary statistics and visualizations. He explains how to create predictive models using both linear regression andXGBoost, and wraps up the course with a look at hypothesis testing. If you’re interested in exploring statistics using a code-first approach, join Matt in this course as he shows you how to use Python to unlock the power of data.

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Matt Harrison

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Linkedin Learning

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.