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Learn to use Python to unlock the power of data and use it to inform decisions.
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Overview
Syllabus
Introduction
- Being a Python statistics MVP
- What you should know
- Using GitHub Codespaces with this course
- Loading data
- Strings and categories
- Cleaning numbers
- Shrinking numbers
- Challenge: Clean Ames
- Solution: Clean Ames
- 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
- Linear regression
- Interpreting linear regression models
- Standardizing values
- Regression with XGBoost
- Challenge: Predict Ames
- Solution: Predict Ames
- Exploring data
- Visualizing distributions
- Running statistical tests
- Testing for normality
- Challenge: Checking square footage distributions
- Solution: Checking square footage distributions
- Next steps
Taught by
Michele Vallisneri
