Machine Learning in GIS : Understand the Theory and Practice

Machine Learning in GIS : Understand the Theory and Practice udemy course

Apply machine learning in Geographic information systems and Remote Sensing in QGIS and Google Earth Engine

Are you eager to harness the power of Machine Learning for geospatial analysis, but not sure where to start? Welcome to our course, designed to equip you with the theoretical and practical knowledge of Machine Learning applied in the fields of Geographic Information Systems (GIS) and Remote Sensing. Whether you're interested in land use and land cover mapping, classifications, or object-based image analysis, this course has you covered.

Course Highlights:

• Theoretical and practical understanding of Machine Learning applications in GIS and Remote Sensing

• Application of Machine Learning algorithms, including Random Forest, Support Vector Machines, and Decision Trees

• Completion of a full GIS project with hands-on exercises

• Utilization of cloud computing and Big Data analysis through Google Earth Engine

• Ideal for professionals across various fields

• Step-by-step instructions and downloadable practical materials

Course Focus:

This comprehensive course delves into the realm of Machine Learning in geospatial analysis, offering a blend of theory and practical application. Upon course completion, you will possess the knowledge and confidence to harness Machine Learning for a wide range of geospatial tasks.

What You'll Learn:

• Installing open-source GIS software (QGIS, OTB toolbox) and proper configuration

• Navigating the QGIS software interface, including components and plug-ins

• Classifying satellite images with diverse Machine Learning algorithms (e.g., Random Forest, Support Vector Machines, Decision Trees) in QGIS

• Conducting image segmentation in QGIS

• Preparing your inaugural land cover map using the cloud computing platform Google Earth Engine

Who Should Enroll:

This course caters to a diverse audience, including geographers, programmers, social scientists, geologists, and any professionals who employ maps in their respective fields. If you anticipate tasks that demand state-of-the-art Machine Learning algorithms for tasks like land cover and land use mapping, this course empowers you with the skills to address such geospatial challenges.

INCLUDED IN THE COURSE: Gain access to step-by-step instructions, practical materials, datasets, and guidance for hands-on exercises in QGIS and Google Earth Engine. Enroll today to unlock the potential of Machine Learning for geospatial analysis!