Level 3 of 3
Advanced Level
Prerequisites
Data Science Intermediate level, or equivalent: survey analysis, pandas wrangling, hypothesis testing and regression. Basic SQL is helpful.
Duration
12 weeks · 140 guided hours · 6 modules. Taught live by an instructor — online or in person.
By the end of this level you can
- Design and interpret causal analyses and programme evaluations
- Apply predictive models appropriately within data science projects
- Work with larger, spatial and text data
- Govern data and analyses responsibly and reproducibly
- Lead a complete, decision-focused data science project
Modules
- 1Module 1 · 22 h · 4 lessonsCausal Inference and Programme Evaluation
- 2Module 2 · 22 h · 4 lessonsPredictive Modelling in Data Science Projects
- 3Module 3 · 22 h · 4 lessonsWorking with Larger and Spatial Data
- 4Module 4 · 20 h · 4 lessonsText Data and Open-Ended Responses
- 5Module 5 · 24 h · 4 lessonsData Governance and Responsible Data Science
- 6Module 6 · 30 h · 5 lessonsData Science Capstone
Advanced level project
Impact and Targeting Analysis for a Cash Assistance Programme
Using provided synthetic programme, survey and spatial data, estimate the programme's effect on food consumption with a quasi-experimental design, map needs by area, analyse open-ended feedback and recommend targeting changes.
Deliverables
- A causal analysis with a stated design, assumptions checks and sensitivity analysis
- Maps and tables of need by area built from spatial data
- A coded summary of open-ended beneficiary feedback
- A reproducible repository, a decision memo and a technical appendix
Assessed on
- The causal design suits the data and its assumptions are checked and stated
- Spatial and text analyses are correct and add genuine insight
- Privacy and data governance requirements are met throughout
- The memo gives a clear, evidence-based recommendation with its uncertainty
All levels are taught live by an instructor — online or in person — see registration options.