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School of Data Science

Turn data into evidence people can use.

The School of Data Science develops practical capability across analysis, visualisation, Python, SQL and data engineering. The focus is not simply on learning tools. It is on using data carefully enough to answer questions, explain patterns and support better decisions.

African data analyst reviewing dashboards and notes at a professional workstation.

The discipline

Capability you can recognise in the work.

Each School is organised around practical capability areas that learners can apply, explain and improve across its programmes.

01
Data preparationClean, reshape and combine source data with a repeatable process.
02
Analytical reasoningFrame useful questions, examine patterns and interpret results carefully.
03
Visual communicationChoose forms of presentation that make the evidence easier to understand.
04
Reproducible workBuild workflows that can be reviewed, repeated and improved over time.

Programmes

Choose the capability you want to build next.

Excel + Power BI

Data Analysis & Visualisation with Excel and Power BI

Learn to clean and shape data with Power Query, model it with DAX, design dashboards people can use, and communicate findings with confidence.

8-week live cohortView ↗
Python + SQL

Data Analysis with Python

Learn to clean and combine datasets with pandas, explore patterns with visualisations, use SQL for data access and joins, and automate routine analysis.

8-week live cohortView ↗
Pipelines + Data Systems

Data Engineering

Develop the practical thinking behind moving, transforming and organising data so analysts, products and reporting systems can depend on it.

Live cohortView ↗