This module focuses on practical skills for working with geospatial data in QGIS. Learners will learn to download and work with shapefiles, including styling vector and raster data. The module also covers handling attribute data using tools like the Field Calculator and selecting features within QGIS.

This module covers cartographic techniques and tools available in QGIS for map representation and styling. Learners will explore coordinate systems, projections, and create various thematic maps such as choropleth, graduated symbol, heat maps, and dot distribution maps. Additionally, the module covers map layout techniques and essential data integration and analysis tools within QGIS.

This module focuses on georeferencing and digitization techniques using QGIS. Learners will understand the process of georeferencing toposheets, including downloading and setting transformation parameters. They will also explore digitization techniques for creating point, polyline, and polygon datasets from toposheets.

This module focuses on advanced techniques for digitizing and georeferencing spatial data from online sources using QGIS. Learners will explore methods for digitizing point, polyline, and polygon datasets from OpenStreetMap and Google Earth images. The module covers downloading and georeferencing Google Earth images, and using the QuickMapServices plugin for accessing map data.

This module explores advanced spatial analysis techniques available in QGIS. Learners will delve into buffer analysis methods including multi-distance buffers, overlay analysis techniques, and network analysis using tools like the ORS (OpenRouteService) plugin. The module equips learners with skills to perform sophisticated spatial analyses for diverse applications.

This module focuses on acquiring and classifying satellite data using QGIS. Learners will explore various satellite data downloaders including USGS, Copernicus, NASA Earth Data Search, and Bhuvan. The module covers supervised classification techniques using the Maximum Likelihood Algorithm, unsupervised classification methods such as K means clustering, and temporal analysis techniques for change detection.

This module covers terrain analysis and surface modeling techniques using QGIS. Learners will explore elevation and slope analysis, hillshade, aspect, contour generation, watershed analysis, surface analysis, viewshed analysis, and profiling and cross-sectioning techniques for detailed spatial analysis and visualization.

This module explores advanced topics in geospatial mapping and application development using QGIS. Learners will learn techniques for extracting building footprints, creating 3D maps, and developing web and mobile maps. The module also covers integrating QGIS with Building Information Modeling (BIM) for creating digital twins.