
Applied GIS Course
Master the full GIS workflow — from spatial data management and cartographic design to advanced raster analysis and Python automation. This applied course equips you with the technical skills professionals use daily across environmental, infrastructure, and planning fields. Build real project experience and deliver analysis that drives decisions.
What you will learn:
Apply vector and raster analysis methods to answer complex spatial questions with confidence.
Design and produce professional maps that communicate spatial data clearly to any audience.
Build and manage geodatabases with structured schemas, domains, and relationship classes.
Automate repetitive GIS tasks using ModelBuilder and Python scripting with arcpy or PyQGIS.
Conduct terrain, hydrological, and suitability analyses using digital elevation models.
Deliver complete GIS projects with technical documentation, stakeholder maps, and recommendations.
How you study in practice Applied GIS Course
How you practice Applied GIS Course
For companies looking to train their teams
With Dedika for businesses, the course includes exercises and examples tailored to your own business and the way your company needs.
Course Content
8 Chapters • 38 LessonsDuration between 4 and 360 hours (you decide)
Chapter 1HideHide detailsSee detailsFoundations of GIS and Spatial Thinking
Foundations of GIS and Spatial Thinking
Lesson 1 • GIS Software Environments
Surveys desktop, web, and open-source GIS platforms and their interfaces. Students identify the right tool for different professional contexts.
Lesson 2 • What GIS Is and Why It Matters
Defines GIS, its core components, and its role across industries. Establishes the conceptual baseline for all subsequent technical work.
Lesson 3 • Spatial Thinking and Geographic Concepts
Introduces spatial reasoning, location, distance, and pattern recognition. Develops the mental framework needed to interpret geographic phenomena.
Lesson 4 • Coordinate Systems and Map Projections
Explains how Earth's surface is mathematically represented in GIS. Students gain ability to select appropriate coordinate systems for their projects.
Chapter 2HideHide detailsSee detailsGIS Data Types and Data Management
GIS Data Types and Data Management
Lesson 1 • Vector Data Model
Covers points, lines, and polygons as representations of geographic features. Connects data model choice to analytical accuracy and storage efficiency.
Lesson 2 • Data Quality and Metadata
Addresses accuracy, completeness, consistency, and lineage of spatial data. Students evaluate dataset fitness before committing to analysis.
Lesson 3 • Organizing and Managing GIS Projects
Establishes folder structures, naming conventions, and geodatabase organization. Students maintain reproducible, shareable project environments.
Lesson 4 • Acquiring and Importing Spatial Data
Teaches methods for obtaining data from open portals, APIs, and field collection. Students can import and validate datasets in a GIS environment.
Lesson 5 • Raster Data Model
Explains grid-based spatial data, cell values, and resolution. Students understand when raster is preferable to vector for continuous phenomena.
Chapter 3HideHide detailsSee detailsCartographic Design and Map Production
Cartographic Design and Map Production
Lesson 1 • Symbolization and Color Theory
Teaches symbol selection, color schemes, and classification methods for thematic maps. Students match visual variables to data types and map purpose.
Lesson 2 • Labeling and Annotation
Addresses automated labeling rules and manual annotation for clarity. Students produce maps where text enhances rather than clutters spatial content.
Lesson 3 • Exporting and Sharing Maps
Covers output formats, resolution settings, and sharing platforms. Students deliver maps in formats appropriate for print, web, and presentation.
Lesson 4 • Map Elements and Layout Design
Covers essential map elements including title, legend, scale bar, and north arrow. Students assemble complete, publication-ready map layouts.
Lesson 5 • Principles of Cartographic Design
Covers visual hierarchy, figure-ground, and map balance. Grounds design decisions in established cartographic theory for professional output.
Chapter 4HideHide detailsSee detailsSpatial Data Editing and Digitizing
Spatial Data Editing and Digitizing
Lesson 1 • Georeferencing Raster Data
Teaches alignment of scanned maps and imagery to a coordinate system using control points. Students produce georeferenced rasters ready for overlay and digitizing.
Lesson 2 • Editing Existing Vector Features
Covers tools for modifying geometry and attributes of existing features. Students correct errors and update datasets to reflect current conditions.
Lesson 3 • Digitizing from Imagery and Basemaps
Teaches on-screen digitizing of points, lines, and polygons from aerial and satellite imagery. Students create new vector layers aligned to real-world features.
Lesson 4 • Topology Rules and Validation
Introduces topology rules that enforce spatial integrity between features. Students identify and fix topological errors before data is used in analysis.
Chapter 5HideHide detailsSee detailsSpatial Analysis: Vector Methods
Spatial Analysis: Vector Methods
Lesson 1 • Spatial Joins and Table Operations
Covers spatial joins, table joins, and field calculations for enriching datasets. Students link attribute information across layers based on location.
Lesson 2 • Geoprocessing Overlay Tools
Teaches clip, intersect, union, erase, and identity operations on vector layers. Students combine datasets to reveal spatial relationships and patterns.
Lesson 3 • Dissolve, Merge, and Append Operations
Explains tools for combining and simplifying feature datasets. Students streamline datasets and prepare inputs for downstream analysis.
Lesson 4 • Proximity and Buffer Analysis
Covers buffer creation, multiple-ring buffers, and near-distance calculations. Students quantify spatial relationships based on distance thresholds.
Lesson 5 • Querying and Selecting Features
Covers attribute queries, spatial selections, and combined query methods. Students isolate relevant subsets of data for targeted analysis.
Chapter 6HideHide detailsSee detailsSpatial Analysis: Raster Methods
Spatial Analysis: Raster Methods
Lesson 1 • Raster to Vector Conversion and Integration
Covers converting raster outputs to vector features and integrating both data models. Students combine raster analysis results with vector datasets for comprehensive outputs.
Lesson 2 • Terrain Analysis from Digital Elevation Models
Derives slope, aspect, hillshade, and curvature from elevation data. Students characterize terrain for environmental, engineering, and planning applications.
Lesson 3 • Raster Calculator and Map Algebra
Introduces cell-by-cell mathematical operations across raster layers. Students combine rasters to create derived datasets for multi-criteria analysis.
Lesson 4 • Reclassification and Suitability Modeling
Covers reclassifying raster values and weighting layers for suitability analysis. Students build weighted overlay models to rank locations by multiple criteria.
Lesson 5 • Hydrological Analysis
Applies DEM-based tools to delineate watersheds, stream networks, and flow accumulation. Students model water movement across landscapes for resource management.
Chapter 7HideHide detailsSee detailsGeodatabases and Spatial Data Workflows
Geodatabases and Spatial Data Workflows
Lesson 1 • Data Sharing and Interoperability
Addresses data exchange formats, web services, and interoperability standards. Students publish and consume spatial data across platforms and organizations.
Lesson 2 • Geodatabase Design and Structure
Covers feature datasets, feature classes, domains, and subtypes in geodatabase design. Students create structured, rule-enforced data schemas for organizational use.
Lesson 3 • Geoprocessing Automation with ModelBuilder
Introduces ModelBuilder for creating visual geoprocessing workflows. Students automate multi-step analyses and share repeatable processes with colleagues.
Lesson 4 • Relationship Classes and Data Integrity
Teaches relationship classes that link tables and enforce referential integrity. Students model real-world associations between spatial and non-spatial data.
Lesson 5 • Introduction to Python Scripting for GIS
Covers Python basics and the arcpy or PyQGIS library for GIS automation. Students write scripts to batch-process datasets and extend GIS functionality.
Chapter 8HideHide detailsSee detailsApplied GIS Projects and Professional Practice
Applied GIS Projects and Professional Practice
Lesson 1 • Environmental and Land Use Analysis
Applies GIS to analyze land cover change, habitat connectivity, and environmental impact. Students produce evidence-based assessments for planning and conservation decisions.
Lesson 2 • Site Suitability and Location Analysis
Applies overlay, raster suitability, and proximity methods to real site-selection problems. Students produce ranked location recommendations supported by spatial evidence.
Lesson 3 • Documenting and Presenting GIS Work
Teaches technical reporting, map series production, and stakeholder presentation skills. Students communicate spatial findings clearly to both technical and non-technical audiences.
Lesson 4 • Infrastructure and Network Analysis
Covers network datasets, routing, and service area analysis for infrastructure planning. Students optimize routes and assess coverage gaps in transportation or utility networks.
Lesson 5 • Defining a GIS Project Scope
Covers problem definition, stakeholder needs, data requirements, and deliverable planning. Students translate real-world questions into structured GIS project plans.
Your valid completion certificate
This course is for you:
Environmental scientists: ready to add spatial analysis to their toolkit.
Urban planners: wanting to move beyond basic mapping into real analysis.
Recent geography graduates: looking to turn academic knowledge into job-ready skills.
Civil engineers: needing to integrate location data into infrastructure decisions.
Career changers: drawn to data-driven roles with a geographic dimension.
Land use consultants: aiming to formalize and deepen their GIS capabilities.
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