Corporate PyQGIS Training Course

1. Understanding the PyQGIS library

1. Basics of PyQGIS
2. Core functionalities and uses
3. Differences between PyQGIS and other GIS scripting libraries

2. The relationship between QGIS and PyQGIS

1. How PyQGIS extends QGIS capabilities
2. Examples of PyQGIS enhancing QGIS functionality
3. The integration of PyQGIS with QGIS core

3. Exploring PyQGIS documentation and resources

1. Finding and navigating the official PyQGIS documentation
2. Community resources and forums for learning PyQGIS
3. Essential PyQGIS tutorials and guides for beginners

1. Sources for GIS data

1. Public domain GIS data repositories
2. Commercial sources of GIS data
3. Crowdsourced GIS data platforms

2. Importing data into QGIS

1. Using the QGIS data manager
2. Importing various data formats (vector, raster)
3. Troubleshooting common data import issues

3. Data formats and conversions

1. Overview of GIS data formats (e.g., Shapefile, GeoJSON, KML)
2. Converting between data formats using QGIS
3. Understanding the implications of data conversion

1. Installing QGIS and PyQGIS

1. Step-by-step installation guide
2. Verifying installation success
3. Common installation issues and solutions

2. Configuring the development environment

1. Setting up a Python IDE for PyQGIS development
2. Configuring QGIS Python paths
3. Essential plugins for development

3. Setting up Python plugins

1. Introduction to QGIS Python plugins
2. Plugin installation and management
3. Creating a simple plugin environment

1. Introduction to PyQt

1. Basics of PyQt and its role in QGIS
2. PyQt widgets and controls
3. Setting up a PyQt development environment

2. Building basic GUI applications for QGIS

1. Designing a GUI layout for QGIS plugins
2. Connecting PyQt widgets to perform GIS functions
3. Testing and debugging PyQt applications

3. Connecting GUI elements to GIS functions

1. Signal and slot mechanisms in PyQt
2. Integrating GUI elements with QGIS API
3. Case studies of GUI-driven GIS applications

1. Accessing and manipulating map layers

1. Layer types and properties
2. Adding, removing, and modifying layers programmatically
3. Working with layer attributes and data

2. Working with vector and raster data

1. Understanding vector and raster data operations
2. Performing geometric operations on vector data
3. Analyzing raster data using PyQGIS

3. Spatial analysis with PyQGIS

1. Introduction to spatial analysis techniques
2. Using PyQGIS for spatial queries and analysis
3. Examples of spatial analysis applications

1. Automating startup tasks with Python

1. Creating startup scripts
2. Examples of automation tasks (e.g., loading layers, setting project settings)
3. Managing script execution at startup

2. Customizing QGIS interface with scripts

1. Modifying the QGIS interface elements
2. Adding custom menus and toolbars programmatically
3. Enhancing user experience with interface customizations

1. Overview of processing algorithms in QGIS

1. List of available processing algorithms
2. Understanding algorithm parameters and outputs
3. Batch processing and automation possibilities

2. Automating spatial analysis tasks

1. Creating automated workflows with processing algorithms
2. Scripting for batch processing of GIS data
3. Optimizing spatial analysis with PyQGIS

3. Creating custom processing scripts

1. Developing new processing algorithms with Python
2. Integrating custom algorithms into the QGIS processing framework
3. Sharing and distributing custom processing scripts

1. Plugin development workflow

1. Setting up a development environment for plugin creation
2. Planning and designing a plugin
3. Developing, testing, and debugging plugins

2. Designing user interfaces for plugins

1. Using Qt Designer to create plugin UIs
2. Best practices for UI design in GIS applications
3. Integrating UI with plugin functionality

3. Deploying and sharing plugins

1. Preparing a plugin for deployment
2. Publishing plugins to the QGIS plugin repository
3. Versioning and updating plugins

1. Utilizing external Python libraries with QGIS

1. Popular Python libraries for GIS (e.g., SciPy, NumPy)
2. Integrating libraries with PyQGIS scripts
3. Case studies on the use of external libraries in GIS projects

2. Handling data with Pandas and GeoPandas

1. Introduction to Pandas and GeoPandas for GIS data
2. Examples of data manipulation and analysis
3. Integrating Pandas and GeoPandas with PyQGIS

3. Advanced scripting techniques

1. Working with APIs and web services
2. Asynchronous programming in PyQGIS
3. Performance optimization and memory management

1. Developing advanced processing tools

1. Extending QGIS processing with custom tools
2. Advanced data processing and analysis techniques
3. Integrating third-party libraries and services

2. Integrating plugins with QGIS processing framework

1. Adding custom algorithms to the processing toolbox
2. Creating user-friendly interfaces for processing plugins
3. Managing plugin dependencies and compatibility

1. Configuring actions in QGIS

1. Understanding actions in QGIS
2. Setting up layer and feature actions
3. Examples of custom actions for enhanced interactivity

2. Enhancing data interactivity with Python scripts

1. Linking Python scripts to actions
2. Dynamic data visualization and manipulation
3. Interactive mapping techniques

1. Developing Python scripts outside of QGIS

1. Advantages of standalone scripts
2. Setting up a scripting environment
3. Accessing QGIS libraries from external scripts

2. Integrating standalone scripts with QGIS projects

1. Automating tasks outside the QGIS interface
2. Script execution from within QGIS
3. Sharing and distributing standalone scripts