What is GIS? Definition, history, and real-world applications in agriculture, health, and environment · Spatial thinking: location, distance, pattern, and spatial relationships · Coordinate systems and map projections: geographic vs projected, datum concepts · Types of spatial data: vector (points, lines, polygons) and raster (grids, pixels) · Metadata and spatial data documentation: ISO 19115 standards · GIS applications: agriculture, health, environment, urban planning, disaster management · Introduction to QGIS and ArcGIS Online: installation, interface, plugins, project setup · Overview of free spatial data sources: OpenStreetMap, GADM, SRTM, WorldPop

GPS field data collection: devices, accuracy, and data recording methods · ODK and KoboToolbox for spatial data: geopoint, geotrace, and geoshape question types · Importing GPS and ODK data into QGIS: CSV coordinates, GPX, and KML files · Downloading satellite imagery: Copernicus Open Access Hub, USGS Earth Explorer · Vector data operations: creating, editing, and attributing features · Raster data management: importing, clipping, reprojecting, and resampling · Spatial databases: PostGIS and SpatiaLite — storing and querying with SQL · Data quality in GIS: positional accuracy, topological errors, and validation · Hands-on lab: collect GPS field data with ODK and create a field survey map in QGIS

Principles of map design: visual hierarchy, colour, generalisation, and balance · Thematic maps: choropleth, graduated symbol, dot density, and proportional symbol · Map elements: title, legend, north arrow, scale bar, source, and projection note · Colour in cartography: sequential, diverging, and qualitative colour schemes (ColorBrewer) · Layout design in QGIS: print layout, map frames, legends, and export settings · Multi-map layouts: inset maps, overview maps, and multi-panel comparisons · Map export: PDF, PNG, and SVG for reports, policy briefs, and presentations · Designing maps for different audiences: technical, policy, and public communication · Hands-on lab: produce three professional-quality thematic maps from a provided dataset

Vector spatial analysis: buffer, clip, intersect, union, dissolve, and spatial join · Point pattern analysis: kernel density estimation and nearest neighbour · Network analysis: shortest path, service area, and routing in QGIS · Raster analysis: map algebra, slope, aspect, hillshade from digital elevation model · Terrain analysis: watershed delineation and flow accumulation · Interpolation: IDW, Kriging, and spline — continuous surfaces from point data · Zonal statistics: summarising raster values within polygon boundaries · Site suitability analysis: multi-criteria evaluation (MCE) for land use decisions · Hands-on lab: site suitability analysis for an agricultural or infrastructure project

Electromagnetic spectrum and remote sensing principles: how satellites see the Earth · Optical sensors: Landsat 8/9, Sentinel-2, MODIS — spatial, spectral, temporal resolution · SAR: Sentinel-1 — all-weather, day/night imaging · Downloading and preprocessing imagery: atmospheric correction and cloud masking · Band combinations and indices: NDVI, NDWI, EVI, SAVI for vegetation and water analysis · Land Use and Land Cover (LULC) classification: supervised and unsupervised methods · Change detection: before-after analysis and multi-temporal image comparison · Crop mapping: agricultural field delineation and crop type identification · Flood and drought monitoring: satellite imagery for disaster response · Introduction to Google Earth Engine: JavaScript basics for large-scale Earth observation · Hands-on lab: calculate NDVI from Sentinel-2 and map vegetation change over time

Agricultural GIS: crop mapping, yield estimation, pest spread, agro-climatic zoning · Precision agriculture: field monitoring, UAV/drone data, and variable rate applications · Food security mapping: IPC maps and spatial food security analysis · Public health GIS: disease mapping, health facility accessibility, outbreak analysis · Malaria and vector-borne disease: spatial risk models and intervention targeting · WASH GIS: facility mapping, sanitation coverage, and water access analysis · Disaster risk mapping: flood zones, landslide susceptibility, humanitarian response · CGIAR spatial research: GIS use in IITA, CIMMYT, IRRI, and ILRI programmes · Hands-on lab: map health facility accessibility or crop suitability for a development context

ArcGIS Online: cloud-based GIS, web maps, story maps, and dashboards for sharing · Python for GIS: GeoPandas, Shapely, Fiona, and Rasterio for automated spatial workflows · Spatial statistics: Moran’s I (spatial autocorrelation) and hotspot analysis (Getis-Ord Gi*) · Joining GIS results with statistical analysis in STATA and R · Writing a GIS technical report: methodology, maps, discussion, and limitations · Capstone project: choose a topic (agricultural mapping, health access, LULC change, or flood risk) — collect or download data, conduct spatial analysis, produce 3+ professional maps, and write a technical report

Collect, manage, and analyse spatial data using QGIS, ArcGIS Online, and Google Earth Engine · Produce professional-quality cartographic outputs for research, policy, and field operations · Analyse satellite imagery to map land cover, vegetation, agricultural areas, and water bodies · Process UAV/drone data using OpenDroneMap to produce orthomosaics, DSMs, and point clouds · Apply GIS to agricultural research, public health, disaster management, and development · Conduct spatial statistics including Moran’s I, kernel density, and multi-criteria suitability analysis · Achieve a credential aligned to ESRI ArcGIS Associate, OSGeo QGIS, CGIAR, and FAO spatial standards

Complete all 7 modules, pass a proctored examination (minimum 75%), and submit a GIS project including at least 3 original maps, a spatial analysis with statistical outputs, and a 1,500-word technical report.

GIS Analyst, Remote Sensing Specialist, Spatial Data Analyst, Land Use Planner, Environmental GIS Officer, Agricultural GIS Analyst, Disaster Risk Analyst, CGIAR/FAO/World Bank GIS Officer. Average starting salary: $45,000–$85,000 USD.