What you would learn in Machine Learning in GIS and Remote Sensing: 5 Courses in 1?
This course will provide you with practical and theoretical knowledge about Machine Learning and Deep Learning in QGIS and ArcGIS used for geospatial analysis. This includes Geographic Information Systems (GIS) and Remote Sensing. At the end of the course, you'll be confident and fully aware of how machines as well as Deep Learning applications in Remote Sensing & GIS technology and how to utilize machines as well as Deep Learning algorithms for various Remote Sensing & GIS tasks, including the land use and cover map (classifications) and the analysis of images based on objects (segmentation or detection of objects) as well as regression modeling within QGIS along with ArcGIS software. The course can also train you to use GIS, an open-source and free tool (QGIS), and the market-leading program (ArcGIS).
The course will help users who are using QGIS and ArcGIS to perform fundamental geospatial analysis/GIS/Remote sensing analysis to carry out additional complex geospatial analytics tasks such as the analysis of images based on the object with a range of information sources and using Deep Learning & Machine Learning modern techniques. In addition to becoming proficient in QGIS for spatial analysis of data, you will be introduced to a different powerful toolbox for processing that is called Orfeo Toolbox and the fantastic abilities that are available in ArcMap as well ArcGIS Pro!
In this course, you will learn to use Machine Learning algorithms such as Random Forest and Support Vector Machines Decision Trees, Convolutional Neural Networks (and others) for Remote Sensing and geospatial tasks. Learn how to perform regression modeling for GIS tasks using ArcGIS. In addition, you will also learn about GIS and Remote Sensing by completing two separate GIS projects while investigating the potential of Machine Learning and Deep Learning analysis in QGIS and ArcGIS.
This course is distinct from other resources for training. Each lecture aims to improve the quality of your GIS and remote sensing abilities in a simple and easy-to-follow way and offer practical solutions. It will be possible to begin studying the spatial data you need for your work and get acclaim from future employers for the latest GIS and Remote Sensing abilities and knowledge of modern geospatial techniques.
This course is suitable for professionals like programmers, geographers as well as geologists, social scientists, GIS and Remote Sensing experts, and any other professionals who have to make use of maps in their work and wish to learn how to use Machine Learning in GIS.
A vital aspect of the course is the activities. The students will receive specific instructions and data sets to build maps using Machine Learning algorithms using the ArcGIS and QGIS software tools.
Content of the Course:
Learn the fundamentals of Machine Learning and Machine Learning in GIS
Discover the most well-known open-source GIS as well as Remote Sensing software tools (QGIS SCP, QGIS, OTB toolbox)
Learn about the industry-leading GIS program ArcGIS (ArcMap) along with ArcGIS Pro
Learn more about supervision and unsupervised learning as well as their applications to GIS
Apply Machine Learning for image classification to image classification in QGIS and ArcGIS.
Run segmentation, and object-based image evaluation within QGIS and ArcGIS
Apply and learn regression modeling to GIS tasks
Know the most important advancements in the area of Artificial Intelligence, deep learning, and machine learning that can be applied to GIS
Do two independent research projects related to Machine Learning and Deep Learning.
Learn about the fundamentals in deep learning, a component of machine learning
Use deep learning algorithms, such as convolution neural networks, in GIS using ArcGIS Pro.
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