Loading…
Loading…
Turn data into decisions with statistics and code
Online or on campus
Data Analytics at Brigant combines statistical theory with hands-on coding in Python and SQL. You will clean real-world datasets, build dashboards, and interpret findings for business and policy audiences. Modules cover probability, regression, experimental design, and introductory machine learning. Campus seminars use anonymised datasets from public health, finance, and education partners. Communication skills are emphasised — analysts must explain uncertainty, not just produce charts.
Access to Brigant's analytics sandbox includes JupyterHub, Tableau licences, and faculty office hours in the Data Studio.
Faculty spotlight
Dr. Priya Sharma teaches Statistical Modelling; Professor Daniel Mensah leads the Causal Inference reading group.
Study online
Every programme can be completed fully online with zero tuition fees — study from anywhere in the world.
On-campus study
Prefer to learn at our Edinburgh campus? On-campus delivery includes tuition fees, in-person seminars, and access to university facilities.
| Code | Course | Credits |
|---|---|---|
| DA101 | Statistics I | 20 |
| DA102 | Programming for Analytics | 20 |
| DA103 | Data Visualisation | 20 |
| DA104 | Business Context for Data | 20 |
| Code | Course | Credits |
|---|---|---|
| DA201 | Regression & Inference | 20 |
| DA202 | Database & SQL | 20 |
| DA203 | Machine Learning Foundations | 20 |
| DA204 | Analytics Ethics | 20 |
| Code | Course | Credits |
|---|---|---|
| DA301 | Advanced Analytics | 20 |
| DA302 | Capstone Analytics Project | 40 |
Recognised & Accredited
