Preprocessing and Reproducible Pipelines
Learners can build a clean mixed-feature preprocessing and model pipeline that reruns from a fresh state.
Executable courseRead the lesson pages, run the browser practice notebook, and keep the downloadable fallback pack if you want a local copy.
Module sequence
- Why preprocessing belongs inside the experimentUnit 1 · 20-35 minutes
- Missing numeric and categorical valuesUnit 2 · 20-35 minutes
- Scaling numeric featuresUnit 3 · 20-35 minutes
- Encoding categorical featuresUnit 4 · 20-35 minutes
- ColumnTransformer for mixed tabular dataUnit 5 · 20-35 minutes
- Pipelines, fit, transform, and leakage preventionUnit 6 · 20-35 minutes
- Feature engineering with prediction-time disciplineUnit 7 · 20-35 minutes
- Reproducible notebooks, random seeds, and run orderUnit 8 · 20-35 minutes
- Project step: build a clean preprocessing-and-model pipelineUnit 9 · 20-35 minutes
- Activity: Build a Clean Preprocessing PipelinePractice activity · 45-75 minutes
- Module 07 Assessment: Pipeline Reproducibility CheckModule check · 35-50 minutes