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Arcgis course

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Master ArcGIS Pro from the ground up and gain the spatial analysis skills employers are actively looking for. This course covers everything from GIS fundamentals and data management to advanced raster analysis, automation, and web publishing. Whether you are entering the GIS field or expanding your technical toolkit, you will finish ready to confidently solve real geographic problems.

Dedika for students

What your team will master:

You will learn how to navigate ArcGIS Pro, manage spatial data formats, and apply core geoprocessing tools to answer real geographic questions. The course covers coordinate systems, geodatabase design, attribute queries, and both vector and raster analysis techniques. You will build automated workflows using ModelBuilder and ArcPy to eliminate repetitive manual tasks. You will also publish interactive web maps and apps through ArcGIS Online for non-GIS audiences. Supplementary topics include 3D visualisation, network routing, remote sensing, spatial statistics, and field data collection.

How your team learns in practice Arcgis course

How your team practises Arcgis course

Professionals from these companies study at Dedika

ActemiumFR
Nunner LogisticsNL
GT Constructora GeotécnicaCR
Sydel StarBR
Metrô de São PauloBR
Aguas AndinasCL
DSMIN
MeridianbetRS
CDHCN

Course content

8 Chapters • 40 LessonsDuration between 4 and 360 hours (you decide)

Chapter 1See details

Introduction to ArcGIS and GIS Fundamentals

  • Lesson 1 • Overview of the ArcGIS Platform

    Surveys Esri's product family including ArcGIS Pro, Online, and Enterprise. Learners identify which tool fits each task type.

  • Lesson 2 • Creating and Managing Projects

    Explains the ArcGIS Pro project structure including geodatabases and folder connections. Learners create, save, and organise a project correctly.

  • Lesson 3 • Navigating the ArcGIS Pro Interface

    Covers the ribbon, panes, map view, and catalogue. Learners gain confidence moving through the interface without external guidance.

  • Lesson 4 • Installing and Configuring ArcGIS Pro

    Guides installation, licensing activation, and initial environment setup. Ensures every learner has a functional workspace before data work begins.

  • Lesson 5 • What Is GIS and Why It Matters

    Defines geographic information systems and their real-world applications. Establishes the conceptual framework that underpins all subsequent ArcGIS work.

Chapter 2See details

Spatial Data Types and Data Management

  • Lesson 1 • Importing and Exporting Data

    Demonstrates importing shapefiles, CSVs, KML, and geodatabase layers. Learners build interoperability skills essential for real project data pipelines.

  • Lesson 2 • Vector Data: Points, Lines, and Polygons

    Explains vector geometry types and their appropriate use cases. Connects geometry choice to accurate spatial representation in later analyses.

  • Lesson 3 • Raster Data Concepts and Formats

    Introduces raster grids, cell resolution, and common file formats. Learners distinguish raster from vector and know when each is appropriate.

  • Lesson 4 • Coordinate Systems and Projections

    Covers geographic vs. projected coordinate systems and datum concepts. Learners reproject data correctly to avoid spatial misalignment errors.

  • Lesson 5 • Geodatabase Design and Management

    Explains file geodatabases, feature datasets, and domains. Learners structure data storage for scalability and integrity.

Chapter 3See details

Symbolising and Visualising Spatial Data

  • Lesson 1 • Working with Basemaps and Layer Blending

    Integrates Esri basemaps and applies layer blending modes for visual depth. Learners enhance map aesthetics without obscuring analytical content.

  • Lesson 2 • Graduated and Proportional Symbology

    Teaches quantity-based rendering using graduated colours and proportional symbols. Learners represent numeric data distributions accurately on maps.

  • Lesson 3 • Creating Map Layouts for Output

    Builds print-ready layouts with map frames, legends, scale bars, and north arrows. Learners produce professional cartographic outputs for reports.

  • Lesson 4 • Labelling Features Effectively

    Configures automatic and manual labels using Maplex label engine. Learners place readable, conflict-free labels on complex feature layers.

  • Lesson 5 • Single Symbol and Unique Value Rendering

    Covers applying uniform symbols and category-based colour schemes. Learners differentiate feature classes visually for clear map communication.

Chapter 4See details

Attribute Data Queries and Table Management

  • Lesson 1 • Select by Attribute Queries

    Builds SQL-based queries to select features meeting defined criteria. Learners isolate subsets of data for targeted analysis and export.

  • Lesson 2 • Joining and Relating Tables

    Performs attribute joins and relates between tables using common key fields. Learners enrich spatial layers with external tabular data sources.

  • Lesson 3 • Understanding Attribute Tables

    Explains table structure, field types, and the relationship between rows and features. Learners read and interpret attribute data linked to spatial features.

  • Lesson 4 • Editing and Calculating Field Values

    Covers field calculator, Python expressions, and batch attribute updates. Learners automate data population and maintain consistent attribute quality.

  • Lesson 5 • Select by Location Operations

    Uses spatial relationships to select features based on proximity or containment. Learners combine attribute and location queries for complex selections.

Chapter 5See details

Spatial Analysis Fundamentals

  • Lesson 1 • Overlay Analysis Techniques

    Applies intersect, union, clip, and erase tools to combine spatial layers. Learners derive new datasets that reflect combined spatial conditions.

  • Lesson 2 • Dissolve and Aggregate Operations

    Merges features by attribute values and aggregates spatial extents. Learners simplify complex datasets while preserving analytical integrity.

  • Lesson 3 • Introduction to Geoprocessing

    Explains the geoprocessing framework, toolboxes, and tool parameters. Learners run tools confidently and interpret results and messages.

  • Lesson 4 • Density and Hot Spot Analysis

    Calculates kernel density and identifies statistically significant clusters. Learners detect spatial patterns and anomalies in point datasets.

  • Lesson 5 • Buffer and Proximity Analysis

    Creates fixed and variable buffers to define influence zones around features. Learners apply proximity analysis to site selection and impact assessment tasks.

Chapter 6See details

Raster Analysis and Surface Modelling

  • Lesson 1 • Viewshed and Line-of-Sight Analysis

    Calculates visible areas from observer points across terrain surfaces. Learners apply viewshed outputs to planning and communication tower siting.

  • Lesson 2 • Interpolation Methods for Continuous Surfaces

    Applies IDW, kriging, and spline interpolation to point data. Learners select appropriate methods based on data distribution and accuracy requirements.

  • Lesson 3 • Raster Reclassification and Map Algebra

    Reclassifies raster values and performs mathematical operations between rasters. Learners build weighted overlay models for multi-criteria decision analysis.

  • Lesson 4 • Slope, Aspect, and Curvature Analysis

    Derives terrain characteristics from elevation surfaces using Spatial Analyst. Learners apply these derivatives to land suitability and hazard assessments.

  • Lesson 5 • Working with Digital Elevation Models

    Loads and visualises DEMs and explores elevation surface properties. Learners understand how terrain data underpins slope, aspect, and viewshed analyses.

Chapter 7See details

Automating Workflows with ModelBuilder and Python

  • Lesson 1 • Introduction to ModelBuilder

    Explains the ModelBuilder canvas, elements, and tool connections. Learners build simple linear models that chain geoprocessing tools automatically.

  • Lesson 2 • Introduction to ArcPy

    Covers ArcPy module structure, environment settings, and running tools via script. Learners execute geoprocessing operations programmatically in Python.

  • Lesson 3 • Scripting Spatial Data Operations

    Writes Python scripts to iterate over datasets, manipulate fields, and manage files. Learners automate repetitive data preparation tasks efficiently.

  • Lesson 4 • Advanced ModelBuilder Techniques

    Introduces iterators, preconditions, and model parameters for dynamic workflows. Learners create flexible models that process multiple datasets automatically.

  • Lesson 5 • Scheduling and Deploying Automated Tasks

    Packages scripts as tools and schedules execution using system task schedulers. Learners deploy production-ready automation for recurring GIS workflows.

Chapter 8See details

ArcGIS Online and Web GIS Publishing

  • Lesson 1 • Creating Web Apps with Instant Apps

    Deploys configurable web apps using Instant Apps templates. Learners deliver focused spatial experiences tailored to specific user needs.

  • Lesson 2 • ArcGIS Online Organisation Setup

    Configures organisational accounts, roles, and content groups. Learners manage user access and content governance for team-based GIS environments.

  • Lesson 3 • Publishing Feature Layers from ArcGIS Pro

    Publishes hosted feature layers and tile layers to ArcGIS Online. Learners make spatial data accessible for web consumption and collaboration.

  • Lesson 4 • Managing and Updating Online Content

    Covers item management, metadata, and overwriting hosted layers. Learners maintain accurate, up-to-date content in organisational portals.

  • Lesson 5 • Building Interactive Web Maps

    Creates web maps using Map Viewer with pop-ups, filters, and smart mapping. Learners design audience-ready maps without desktop GIS software.

Certification

Your valid completion certificate

This course is for you:

  • Environmental consultant: needs spatial tools to support site assessments and reporting.

  • Urban planning student: building technical credentials before entering the work market.

  • Data analyst: looking to add a geographic dimension to existing analytical work.

  • Career changer: transitioning into GIS from a non-technical professional background.

  • Civil engineer: wants to integrate mapping workflows into infrastructure project pipelines.

  • Public health researcher: needs to visualise and analyse location-based population data.

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