Data Science Advanced
Production-style data science — feature engineering, advanced pandas, time series, JSON/API patterns, data quality, and KPI reporting across 32 lessons and 274+ drills.
Who it's for
Learners who completed Data Science Intermediate and want production-style EDA pipelines before Machine Learning.
What you'll learn
- Engineer features for modeling (encoding, scaling, datetime, text)
- Use query, apply, pipe, and multi-index patterns
- Build rolling and lag features for time series baselines
- Normalize JSON and nested API records
- Validate data quality and optimize memory
- Deliver KPI dashboards, A/B test EDA, and RFM segmentation
- Complete capstones and bridge to Machine Learning
Course contents
- 01Reproducible analyst workflow
- 02Feature engineering for ML-ready tables
- 03Advanced pandas query, apply, pipe
- 04Time series lags, rolling, naive forecast
- 05JSON normalize & API patterns
- 06Data quality, assertions, chunking
- 07Storytelling, KPIs, A/B tests, RFM
- 08Shop BI, academy, forecast capstones + ML bridge