Course catalogue
Search and filter by category, level and format. Every course has modules, exercises and optional assessments. Pricing is negotiable — request a quote from any course.
Turn raw spreadsheets into reliable analysis with lookups, PivotTables, Power Query and clear charts.
Course book available
Prerequisites: Basic Excel navigation (entering data, simple formulas)
Model data, write DAX measures and publish dashboards that leadership teams use every week.
Course book available
Prerequisites: Comfortable with Excel tables and PivotTables
Import, clean, analyse and visualise data in R with the tidyverse, and produce reproducible reports.
Course book available
Prerequisites: No programming experience required
Learn Python from zero and use pandas to analyse real datasets.
Course book available
Prerequisites: No programming experience required
Query relational databases confidently: filter, join, aggregate and build analysis-ready tables.
Prerequisites: None
Understand the statistics behind every report: summaries, sampling, confidence intervals and hypothesis tests.
Prerequisites: Secondary-school mathematics
Model relationships with linear and logistic regression, check assumptions and report results responsibly.
Prerequisites: Descriptive & Inferential Statistics or equivalent
Manage, analyse and document survey and research data in STATA with reproducible do-files.
Prerequisites: Basic statistics
Use IBM SPSS to manage data, run statistical tests and report research results clearly.
Prerequisites: None
Design rigorous studies: research questions, sampling, measurement, analysis plans and ethics.
Prerequisites: Basic statistics recommended
Build XLSForm questionnaires, deploy them to enumerators and manage incoming data in KoBoToolbox.
Prerequisites: Basic Excel
Run high-quality, secure field data collection with SurveyCTO's advanced features.
Prerequisites: XLSForm basics (e.g. KoBoToolbox course)
Write clear, unbiased questions and validate your questionnaire before fieldwork starts.
Prerequisites: None
Detect and fix data problems during fieldwork with high-frequency checks and back-checks.
Prerequisites: Experience with survey data
The full data science workflow — question, data, analysis, model and communication — in one course.
Prerequisites: Basic Python or completion of Python Programming for Data
Systematically explore datasets to find patterns, problems and hypotheses worth testing.
Prerequisites: Python or R basics
Build, tune and evaluate supervised and unsupervised models with scikit-learn.
Prerequisites: Data Science Foundations or equivalent
Build predictive models that support real decisions — forecasting, risk scoring and targeting.
Prerequisites: Machine Learning or equivalent
Use modern AI tools — including large language models — responsibly for analysis, reporting and services.
Prerequisites: Basic Python recommended
Use AutoML tools to speed up model development — while keeping validation and judgement in human hands.
Prerequisites: Machine Learning or equivalent
Create, edit, analyse and map spatial data in ArcGIS Pro.
Prerequisites: Basic computer skills
Organise, clean and maintain spatial databases that teams can trust.
Prerequisites: ArcGIS Pro Essentials or QGIS experience
Answer spatial questions with proximity, hotspot, suitability and raster analysis.
Prerequisites: ArcGIS Pro Essentials
