Data Science
Analyze data, train models, and communicate business impact with Python.
Level
Intermediate
Duration
72 hours
Lessons
61 lessons
Build a churn prediction model and executive dashboard.
Clean and model messy business datasets
Train supervised models and explain tradeoffs
Present findings through executive-ready dashboards
Each module includes practical lessons, time estimates, and project checkpoints.
72 hours total
Build the data cleaning and exploration habits used on real teams.
Clean, reshape, join, and profile business datasets.
Build charts that reveal distributions, cohorts, and anomalies.
Combine product, billing, and event data safely.
Detect missing values, duplicates, leakage, and drift.
Train models and communicate their tradeoffs clearly.
Model continuous outcomes and evaluate residual behavior.
Train classifiers and tune precision, recall, and thresholds.
Use holdouts, cross-validation, and leakage checks.
Explain predictions with interpretable model summaries.
Package analysis into decisions stakeholders can act on.
Create KPI views for product and revenue teams.
Write concise analysis memos with assumptions and caveats.
Run a model review meeting and defend tradeoffs.
Translate model insights into testable product actions.
