All Geospatial Training Courses
at Geo-Learn India

About This Course

Geographic Information Systems (GIS) is the foundational skill of the entire geospatial industry. This comprehensive course takes you from the very basics of what GIS is and how spatial data works, all the way through to professional-level spatial analysis, map production, and real-world applications. Whether you are a student, a researcher, or a professional entering the GIS world for the first time, this course provides the full conceptual and practical toolkit you need to work confidently with spatial data.

The course uses a mix of vector and raster data from real Indian geographic contexts — urban areas, agricultural regions, river basins, and more — so you learn GIS in a way that directly applies to Indian projects and employers.

Course Details

Duration	6–8 Weeks (2–3 sessions/week)
Mode	100% Live Online (Google Meet / Zoom)
Level	Beginner to Advanced — no prior GIS knowledge needed
Software	QGIS (free) + ArcGIS basics
Batch Options	Morning (9–11 AM) · Evening (7–9 PM) · Weekend
Class Recordings	Shared after every session for revision
Certificate	Geo-Learn Certificate on completion
Support	WhatsApp doubt-clearing between sessions

Who Should Enroll

• B.Sc. / M.Sc. students in Geography, Environmental Science, or Earth Sciences
• Engineers in Civil, Environmental, and Agricultural fields needing GIS skills
• Government officers in land records, revenue, forest, or urban planning departments
• Researchers needing spatial data analysis for thesis or field projects
• Anyone starting a career in GIS or geospatial data science in India

Complete Curriculum — 12 Modules

1. 01Introduction to GIS & Geospatial ScienceWhat is GIS, history, components, applications in India — urban planning, agriculture, disaster management
2. 02Coordinate Systems & Map ProjectionsGeographic vs projected CRS, WGS84, UTM, India-specific projections — datum transformations
3. 03Vector Data — Types, Structure & EditingPoints, lines, polygons — shapefile, GeoJSON, KML formats — attribute tables and field calculations
4. 04Raster Data — Concepts & AnalysisRaster structure, resolution, resampling, raster calculator operations and band math
5. 05Spatial Queries & SelectionsSelect by attribute, select by location, query builder — filtering and extracting features
6. 06Geoprocessing ToolsBuffer, clip, union, intersect, dissolve, merge — building automated processing workflows
7. 07Digitization & Data CreationOn-screen digitization, georeferencing scanned maps, GPS data import and attribute entry
8. 08Terrain Analysis & DEM ProcessingSRTM/ASTER DEM — slope, aspect, hillshade, contours, watershed delineation
9. 09Spatial InterpolationIDW, kriging, natural neighbor methods — creating continuous surfaces from point data
10. 10Thematic Map Design & CartographyColor schemes, symbology, labeling, legend design, north arrow, scale bar — print layouts
11. 11GIS Data Sources & OpenData IndiaBhuvan, NRSC OpenData, OSM, Survey of India data — finding and using free Indian geodata
12. 12Capstone ProjectEnd-to-end GIS project on a real Indian dataset — spatial analysis, map production and reporting

Hands-On Projects

• Urban Land Use MappingDigitize and classify land use categories for an Indian city using satellite imagery and census data.
• Flood Risk Zone AnalysisCombine DEM, river network, and land use data to identify flood-prone areas using geoprocessing tools.
• Thematic Map SeriesProduce a professional 3-map series on population density, road connectivity, and soil types for an Indian district.

Skills You Will Gain Tools Covered

About This Course

ArcGIS by Esri is the world’s most widely deployed GIS platform and is the industry standard for government agencies, consulting firms, urban planners, environmental organizations, and research institutions worldwide — and increasingly in India. Proficiency in ArcGIS is a direct requirement in most GIS job descriptions in India today. This course provides deep, practical training in ArcGIS Pro (current generation), ArcMap (legacy, still widely used in India), and ArcGIS Online — covering every major workflow from data management and spatial analysis to advanced cartography and automation.

We assist all enrolled students in accessing an ArcGIS software license for the duration of the course so you can practice fully.

Course Details

Duration	6–8 Weeks (2–3 sessions/week)
Mode	100% Live Online
Level	Beginner to Advanced
Software	ArcGIS Pro 3.x, ArcMap 10.x, ArcGIS Online
License Support	Guidance on accessing ArcGIS student/trial license
Batch Options	Morning · Evening · Weekend
Certificate	Geo-Learn Certificate on completion

Who Should Enroll

• Students and professionals targeting GIS Analyst / Specialist job roles in India
• Urban planners, civil engineers, and environmental managers using Esri tools
• Government GIS departments upgrading from ArcMap to ArcGIS Pro
• Researchers needing professional-grade spatial analysis and map production
• Anyone seeking the industry-standard GIS certification path

Complete Curriculum — 13 Modules

1. 01ArcGIS Pro Interface & Project SetupMaps, scenes, layouts, catalogs — project structure, data connections, licensing
2. 02Data Management & GeodatabaseFile geodatabase, feature classes, domains, subtypes — importing and exporting data formats
3. 03Spatial Analysis ToolboxBuffer, overlay, proximity, statistics — spatial analysis with ArcGIS Pro’s analysis tools
4. 04Raster Analysis in ArcGISRaster calculator, reclassify, zonal statistics, map algebra — surface and terrain analysis
5. 05Network AnalysisClosest facility, service area, route analysis — building and solving network datasets
6. 063D Visualization & ArcScene3D scenes in ArcGIS Pro — extruding features, surface draping, fly-through animations
7. 07Cartographic Design & Map LayoutsAdvanced symbology, annotation, map series, dynamic text — producing print-ready map products
8. 08ModelBuilder Workflow AutomationBuilding geoprocessing models with ModelBuilder — iterators, model parameters, documentation
9. 09ArcGIS Online — Web Maps & DashboardsUploading data, creating web maps, configuring pop-ups, building Operations Dashboards
10. 10Field Data Collection — Survey123Designing forms, collecting GPS-tagged field data, syncing to ArcGIS Online
11. 11ArcGIS Pro Python Scripting (Intro)arcpy basics — running geoprocessing tools from Python, automating repetitive tasks
12. 12ArcMap to ArcGIS Pro MigrationConverting MXD documents, replicating workflows — key differences and transition tips
13. 13Capstone ProjectFull end-to-end GIS project in ArcGIS Pro — analysis, ModelBuilder workflow, map layout, reporting

Skills You Will Gain Tools Covered

About This Course

Google Earth Engine (GEE) is arguably the most powerful freely available platform for large-scale geospatial analysis in the world. It gives you access to petabytes of historical and near-real-time satellite imagery — Landsat, Sentinel, MODIS, and more — all processed on Google’s infrastructure, meaning you can analyze years of data over entire countries without downloading a single file or needing powerful hardware.

This course teaches both the JavaScript Code Editor API and the Python API with the geemap library — covering everything from basic image loading and visualization to advanced time-series analysis, vegetation monitoring, flood and fire mapping, land cover classification, and building interactive web applications. This is the cutting-edge tool used by international climate scientists, IPCC researchers, and global environmental organizations.

Course Details

Duration	6–8 Weeks (2–3 sessions/week)
Mode	100% Live Online
Level	Intermediate to Advanced (basic GIS familiarity helpful)
Platform	GEE Code Editor (JavaScript) + Python geemap
Cost	GEE is free with Google account registration
Batch Options	Morning · Evening · Weekend
Certificate	Geo-Learn Certificate on completion

Who Should Enroll

• Environmental scientists and climate researchers working with satellite data at scale
• GIS professionals wanting to move from desktop to cloud-based geospatial analysis
• Researchers conducting national or regional-scale studies using multi-year satellite datasets
• Python programmers wanting to integrate GEE into data science workflows
• Students and faculty in remote sensing who need cloud processing capabilities

Complete Curriculum — 14 Modules

1. 01GEE Platform Overview & SetupCode Editor interface, GEE architecture, account setup, JavaScript basics for GEE
2. 02Images & Image CollectionsLoading Landsat, Sentinel, MODIS — filtering by date, cloud cover, and spatial bounds
3. 03Visualization & Map DisplayBand combinations, visualization parameters, custom palettes, adding layers to the map
4. 04Spectral Indices in GEEComputing NDVI, EVI, NDWI, NDBI, NBR at scale — mapping over large areas and time periods
5. 05Time-Series Analysis & ChartingMonthly/annual vegetation trend charts — time-series decomposition and anomaly detection
6. 06Image Compositing & MosaickingMedian, mean, greenest pixel composites — seasonal and annual mosaic generation
7. 07Land Cover Classification in GEETraining data collection, Random Forest classifier, accuracy assessment — national-scale LULC
8. 08Flood Mapping with SAR & Optical DataSentinel-1 SAR backscatter analysis — before/after flood comparison and inundation extent mapping
9. 09Urban Heat Island & LST AnalysisLand Surface Temperature from Landsat thermal bands — mapping urban heat islands in Indian cities
10. 10Forest & Fire MonitoringMODIS fire data, NBR-based burn severity mapping — forest loss detection with Hansen GFC data
11. 11GEE Python API with geemapearthengine-api + geemap — Jupyter Notebook workflows, converting JS scripts to Python
12. 12Exporting Data from GEEExporting images and tables to Google Drive, Cloud Storage, and Asset — batch exports
13. 13Building GEE Web ApplicationsGEE App UI — panels, sliders, buttons, charts — publishing and sharing interactive web apps
14. 14Capstone ProjectMulti-year environmental monitoring study — vegetation trends, classification, web app publishing

Skills You Will Gain Platforms & Libraries

About This Course

R is the statistical backbone of spatial research — the language most trusted in academia, environmental science, epidemiology, and government spatial-statistics units for its rigor and reproducibility. This course teaches you to handle, analyse, and visualise spatial data entirely within R, moving well beyond simple mapping into genuine spatial data science: interpolation surfaces, spatial regression, and clustering that answer “why” a pattern exists, not just “where.”

You will work with real Indian datasets — rainfall stations, district-level census data, land cover rasters — using the modern sf and terra packages that have replaced older R spatial tools, producing publication-ready maps and fully reproducible R Markdown reports along the way.

Course Details

Duration	5–7 Weeks (2–3 sessions/week)
Mode	100% Live Online
Level	Beginner to Advanced — R taught from the ground up
Environment	R + RStudio (free & open source)
Packages	sf, terra, ggplot2, tmap, leaflet, gstat, spdep
Batch Options	Morning · Evening · Weekend
Certificate	Geo-Learn Certificate on completion

Who Should Enroll

• M.Sc./Ph.D. researchers who need statistically defensible spatial analysis for a thesis or paper
• Government & NGO analysts working with census, health, or agricultural district-level data
• Environmental scientists building interpolation surfaces from station-based rainfall or pollution data
• GIS professionals who want a statistics-first complement to their ArcGIS/QGIS skills
• Anyone who already knows basic R and wants to extend it into spatial work

Complete Curriculum — 12 Modules

1. 01R & RStudio Setup for Spatial WorkR basics for those new to the language, RStudio IDE, installing the spatial package ecosystem
2. 02sf — Simple Features for Vector DataReading shapefiles/GeoJSON, geometry types, attribute handling, CRS & reprojection with sf
3. 03Spatial Joins, Overlays & Geoprocessingst_join, st_intersection, st_buffer, st_union — replicating GIS geoprocessing tools in code
4. 04terra — Raster Data in RLoading, cropping, masking rasters — raster algebra, resampling, and reclassification
5. 05Thematic Mapping with ggplot2Choropleth maps, custom colour scales, faceted maps, publication-quality cartography
6. 06Interactive Maps — tmap & leafletStatic-to-interactive workflows, view mode in tmap, building leaflet widgets from R
7. 07Spatial Interpolation — IDW & KrigingCreating continuous surfaces from point data (rainfall, soil, pollution) with gstat
8. 08Spatial Autocorrelation — Moran’s ITesting for spatial clustering, neighbourhood weights matrices with spdep
9. 09Geographically Weighted Regression (GWR)Modelling spatially varying relationships — where a driver’s effect changes across space
10. 10Working with Climate & RS Rasters in RNetCDF climate data, NDVI raster time-series, zonal statistics with terra
11. 11Reproducible Reports with R MarkdownCombining maps, stats & narrative into a single reproducible, shareable report/document
12. 12Capstone ProjectEnd-to-end spatial statistics study on an Indian dataset — interpolation, regression, mapped output

Skills You Will Gain Tools & Packages Covered