Data Analysis

From cell to query to model — the analyst's skillset, end to end.

A structured curriculum to take you from spreadsheets to running real analyses on real data. SQL is the foundation; Stata, Python, and R are the working tools of an economist; econometrics is what turns the data into claims that survive scrutiny.

By the end

✓Query any relational database with confidence
✓Use Stata fluently for data wrangling, regression, and panel analysis
✓Write Python and R for analysis, modelling, and visualisation
✓Clean and shape messy data without flinching
✓Run regressions you can defend, and read other people's regressions critically
✓Communicate findings the way decision-makers actually want to hear them

Prereqs

•No prior coding experience required for SQL or Python
•Stata and econometrics assume high-school algebra and basic statistics

Courses

SQL for Analysts

Beginner

From SELECT to window functions. The complete grammar an analyst needs to query, shape, and trust real datasets.

12 modules•~10 hours, self-paced

SQL Intermediate — Analytical Patterns

Intermediate

Bridge from query-writing to analysis. Window functions in depth, CTE pipelines, and the four shapes that cover most working-analyst output: reporting, cohort, funnel, time-series.

8 modules•~8 hours, self-paced

SQL Advanced — Systems and Optimisation

Advanced

Systems-level SQL. Query execution and the planner, index strategy, recursive CTEs, advanced window-frame work, JSON / semi-structured data, materialised views and partitioning, concurrency and locking.

8 modules•~9 hours, self-paced

Python for Economists, A to Z

Beginner

Python from your first variable to a regression on real Kenyan data. Twelve modules built around what an economist actually does with Python: pandas DataFrames, NumPy arrays, statsmodels regressions, matplotlib charts, and the workflow that ties it all together. Every exercise runs real Python in your browser.

12 modules•~12 hours, self-paced

R for Applied Researchers

Beginner

R for the kind of work researchers and policy analysts actually do: data wrangling with the tidyverse, plotting with ggplot2, and modelling with lm and the broom workflow. Twelve modules, every exercise runs real R in your browser via WebR.

12 modules•~12 hours, self-paced

Stata for Economists

Intermediate

The complete Stata workflow used by working economists, policy analysts, and researchers. From loading a .dta file to running fixed-effects panel regressions and exporting publication-ready tables. Twelve modules that cover everything an economist needs to be productive in Stata, with hands-on practice on real Kenyan datasets.

12 modules•~12 hours, self-paced

Econometrics from First Principles

Intermediate

OLS, identification, and the toolkit that turns data into causal claims you can defend. Twelve modules from the linear regression to instrumental variables, panel data, and time series — with the assumptions, the failure modes, and the recipes for spotting bad inference in published work.

12 modules•~14 hours, self-paced

Data Visualization & Storytelling

Mixed

Charts that change minds. The grammar of graphics, the principles Tufte taught, and the dashboard discipline that Tableau, Power BI, and the FT graphics desk all share. Built for analysts whose work doesn't get read because the charts don't argue.

10 modules•~9 hours, self-paced

Tableau for Analysts

Mixed

Tableau end-to-end: from connecting messy data through Level-of-Detail expressions, parameter-driven dashboards, and Tableau Server. Built for the analyst who needs to ship publication-grade dashboards employers will respect — not just toy chart galleries.

12 modules•~12 hours, self-paced

Power BI for Analysts

Mixed

Power BI end-to-end: Power Query for ETL, the data model with star schemas, DAX from CALCULATE through time intelligence, and Power BI Service for governance. Built for the analyst at a Microsoft shop who'll be the in-team Power BI authority within six months.

12 modules•~12 hours, self-paced