Python Statistics Essential Training

Offered By: LinkedIn Learning

Tags

Python Courses Statistics & Probability Courses Data Analysis Courses Data Visualization Courses pandas Courses Jupyter Notebooks Courses Data Cleaning Courses Statistical Modeling Courses Hypothesis Testing Courses Statistical Inference Courses

Course Description

Overview

Learn to use Python to unlock the power of data and use it to inform decisions.

Syllabus

Introduction

Being a Python statistics MVP
What you should know
Using GitHub Codespaces with this course

1. Loading and Cleaning Data

Loading data
Strings and categories
Cleaning numbers
Shrinking numbers
Challenge: Clean Ames
Solution: Clean Ames

2. Exploring and Visualizing

Categorical exploration
Histograms and distributions
Outliers and Z-scores
Correlations
Scatter plots
Visualizing categorical and numerical values
Comparing two categoricals
Challenge: Explore Ames
Solution: Explore Ames

3. Linear Regressions

Linear regression
Interpreting linear regression models
Standardizing values
Regression with XGBoost
Challenge: Predict Ames
Solution: Predict Ames

4. Hypothesis Tests

Exploring data
Visualizing distributions
Running statistical tests
Testing for normality
Challenge: Checking square footage distributions
Solution: Checking square footage distributions

Conclusion

Next steps

Taught by

Michele Vallisneri

Related Courses

Computational Investing, Part I
Georgia Institute of Technology via Coursera Введение в машинное обучение
Higher School of Economics via Coursera Математика и Python для анализа данных
Moscow Institute of Physics and Technology via Coursera Introduction to Python for Data Science
Microsoft via edX Python for Data Science
University of California, San Diego via edX