Data Science
Wrangle, analyze, and engineer data.
Working with Data using Pandas
A gentle, topic-by-topic intro to pandas — Series, DataFrames, filtering, computed columns, and groupby — before the full Pandas for Data Analysis course.
R Foundations
A from-zero R course — vectors, matrices, control flow, pipes, data frames, joins, reshaping, descriptive stats, and base plotting across 35 live, auto-graded lessons.
SQL Foundations
A comprehensive from-zero SQL course — SELECT, filtering, aggregates, joins, subqueries, UNION, and modifying data — 30 lessons of live, auto-graded SQLite queries in your browser.
Data Science Beginner
Interactive-first data science with Python: NumPy, pandas, matplotlib, and academy datasets — 260+ graded drills, 32 playgrounds, 32 lessons.
Data Science Intermediate
Multi-table pandas analysis: tidy data, cleaning, merge, groupby advanced, seaborn, light scipy stats, datetime, and capstone projects — 270+ drills, 32 playgrounds, 32 lessons.
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.
Statistics with R
A comprehensive base-R statistics course — descriptive analysis, probability, confidence intervals, hypothesis tests, correlation, regression, and ANOVA across 30 self-paced lessons.
Time Series
Build intuition for forecasting — decomposition, ACF/PACF, stationarity, and ARIMA — as interactive concepts plus guided deep dives.
Data Engineering
The data structures and distributed-systems ideas behind every pipeline — hash tables, LSM-trees, B-trees, the Kafka log, MapReduce, and CAP — interactive.
Databricks & Delta Lake
How the lakehouse really works — the Delta transaction log, OPTIMIZE/Z-order, MERGE & SCD2, Catalyst, AQE, Photon, and Unity Catalog — interactive.