Learning paths
Each path groups courses in a recommended order, with prerequisites, objectives and practical assignments. Progress updates as you complete lessons.
Go from spreadsheet user to confident analyst: clean data, query it, summarise it and report it.
Design questionnaires, run digital data collection and deliver clean survey data.
Design studies and analyse research and survey data with rigour, in STATA, SPSS or R.
Build the KPI frameworks, data models and dashboards organizations use to steer performance.
Map, manage and analyse spatial data for planning, agriculture, health and environment.
Build, validate and apply predictive models — and communicate them responsibly.
Not sure where to start?
See a roadmap with stages, courses, projects and practice questions.
Your roadmap · Data Analyst
Analysts turn raw data into answers: they clean, query, summarise and explain what the numbers mean.
Foundations
Indicative: 4–6 weeks
Spreadsheets, data cleaning and descriptive statistics
Core tools
Indicative: 6–8 weeks
SQL and a programming language for analysis
Practical projects
Practice questions
Durations are indicative and depend on your starting point and weekly study time. Training builds skills; it cannot guarantee employment.
View the full learning path