Path1 course
Monitoring & Evaluation Officer
The core track for a new M&E officer — indicator definition, routine data quality, and reporting that survives a donor review, taught in both Python and R.
Cassion Learning Ecosystem
The number in your report
should mean what you say it means.
Data analysis with Python and R, taught on the data you actually work with: CommCare form dumps, KoboToolbox exports, DHIS2 aggregates, and the messy registers behind them. Built for monitoring and evaluation, public health, nutrition, humanitarian, education and NGO programme work.
Learn
Start from the job you hold or the one you are moving toward. Each path names its competencies and how they are assessed.
All pathsCourses
Every technique is taught in Python and in R, because M&E teams are split across both.
All coursesDatasets
Every dataset ships a data dictionary, provenance, quality notes, and worked examples in both languages. All are synthetic or de-identified.
All datasetspublic-health5,472 rows
Routine vaccination coverage — district reporting, 2024
Synthetic monthly DHIS2-style aggregate reporting of routine immunisation doses across 38 health facilities, with deliberate reporting gaps.
nutrition4,200 rows
MUAC screening — Artibonite, 2024
Synthetic mid-upper arm circumference screening records for 4,200 children under five across twelve communes, generated to mirror CMAM admission patterns.
education68,000 rows
School attendance and dropout — 2024 school year
Synthetic daily attendance records for 6,800 students across 24 schools, structured to support dropout risk and school feeding analysis.