This course builds core skills for reproducible research.
- Build reproducible research projects and workflows
- Create compelling visual arguments
- Draw useful conclusions from data and model results
3 - Reproducable & collaborative research with git
5 - Efficient code that does not break
6 - Data visualization & summary analysis
- Counting <legislator letters example>
- Matching <web scraping text example>, <web scraping documents and tables example>, <text reuse example>
- Classification <example>
- Unsupervised <example>
- Supervised Learning <content tagging example, <learning example>
- Clustering <example>
8 - Model results
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Hypothesis testing <Gender pay gap example>
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Interpreting Logit <Sentencing decisions example>
9 - Duration models <Department of Transportation rulemaking example>
10 - Computation