What is GeoAI
You are using GeoAI every day
Everyone has heard of Artificial Intelligence (AI). It’s the automation of tasks based on the learning of behaviors seen in dynamic data to produce new information. The algorithms are self learning and continually discover trends. Add locational prediction and you have GeoAI.
The most common example that you use is vehicle navigation. Big data is compiled from the behaviors of millions of vehicles. Programmed algorithms discover patterns in vehicle routing. These patterns are then conveyed to you as a route that saves you time, gas, and decreases pollution. GeoAI will advance to a whole new level when communicating speed, fueling, and signage to self-driving vehicles.
GeoAI skills are marketable
AI types of jobs will increase by 40% from 2023-2027.
The average salary of a machine learning engineer is $133,226 (365 DataScience report).
There are a combination of technologies that you should be looking to learn:
- APIs – programmer interfaces that allow you to fetch a variety of data
- Python – create scripts that automate data extraction, cleaning, and loading
- R – a package for statistical analysis and graphics
- Google Cloud / AWS – available preconfigured base models to create content or make predictions
- ArcGIS Pro – new GeoAI tools within ArcToolBox to run spatial functions
AI concepts simply explained
Let’s get a handle on 5 other terms that support the creation of GeoAI. We’ll use the simple example of the industry of selling hamburgers. But the same principles apply to any multivariable problem such as tracking spread of disease or reacting to climate change indicators.
Artificial Neural Networks (ANN)
It’s a network made up of multiple nodes where each node has a function determining a simple output. This emulates the way a biological brain fires decisions in animals. The ANN is used to train an AI system on how to think quickly.
Machine Learning (ML)
This is a model used for well-defined tasks with structured data. Outcomes teach the model to make new decisions.
Natural Language Processing (NLP)
This is the machine learning technology that gives computers the ability to interpret, manipulate, and comprehend human language.
Deep Learning (DL)
This is a type of machine learning in which multiple layers of complex tasks can make sense of unstructured data such as posts in the social media sphere.
Ensemble Learning (EL)
An approach in which two or more models are applied to the same data and the predictions of each model are combined.
Led by the best industry experts
Our GIS courses are based on the problems that our instructors are truly solving.
“I want you to feel rewarded by creating actionable insights out of data. There’s an ocean of raw information out there and we need to quickly inform decision makers with the best data science to save our planet. “
-Melissa Anthony, GIS/Data Science Instructor
Bo Wilmer
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Imtiaz Syed
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Our program is job focused
Your mission is to get a GIS job. Our mission is to help you get there. We show you a strategy to get networked into the industry along with teaching you the key skills listed on job announcements. This includes: UAV data processing, spatial analysis, Python scripting, cloud applications, web programming, and more.
Project-based GIS Courses
Complete courses covering spatial analysis, Python scripting, and GIS web development
UAV Data Processing
Learn how to collect, analyze, and visualize UAV data for various applications
Career Networking Strategy
Get connected with industry professionals and explore job opportunities in GIS-driven careers
Spatial Analysis
Utilize cutting-edge tools to analyze and interpret spatial data effectively
Career Services Dashboard
Use our AI driven app to progress through two phases of networking and job application
Python Scripting
Gain hands-on experience in scripting for GIS projects and workflows