What do you want to work on?
Four connected toolkits. Plan and analyse an experiment, measure impact when a clean test is impossible, or sharpen the Python and SQL you use every day.
A/B Testing Calculator
Plan a test, analyse your results, and learn the theory. Picks the right statistical test for your metric, sizes the sample, and gives a plain-English verdict.
- Sample size & duration planner
- Z-test, Welch's t, delta method, SRM check
- Upload Excel / CSV and get a verdict
Causal Inference
How to measure a real effect when you can't run a clean A/B test. Five practical methods, when to use each, their limits, and runnable Python.
- Difference-in-Differences, RDD, IV, matching, synthetic control
- Business cases, not textbook proofs
- Formulas & copy-paste Python you can run
Python for Analysts
Practical Python for product analytics — language fundamentals, dataset design, pandas, and six real cases with runnable code and charts.
- Fundamentals: structures, algorithms, functions
- Dataset design: types, tidy format, clean reads
- Six business cases with real charts
SQL for Analysts
Practice databases and fifteen product tasks — from DAU and conversion to churn, cohorts and window functions.
- Joins, NULL logic, dates, CTE, window functions
- Four linked databases with a visible schema
- 15 tasks from easy to medium, with real output
Built by a product analyst as an open, bilingual learning resource. Everything runs client-side.