ArcGIS : Learn Deep Learning in ArcGIS to advance GIS skills
What you'll learn
- Understand basics of deep learning as a part of machine learning
- Discover the deep learning in ArcGIS Pro
- Apply deep learning algorithms , such as convolution neural networks, in GIS with ArcGIS Pro
- Learn how to install deep learning frameworks for ArcGIS
- Learn about deep learning workflow in general, and all steps in particular
- Understand different deep learning programming frameworks
- Apply deep learning in the practical real-life examples in ArcGIS Pro
- Complete your own deep learning-based project in ArcGIS Pro
- Improve your practical skills in GIS and ArcGIS
- An interest in working with spatial data.
- Prior knowledge of basic spatial data related concepts such as the different data types and coordinate systems
- Access to ArcGIS Pro (version 2.5 or more) and a license for spatial analyst (free trial available on the ESRI website)
Need to take your spatial data (GIS, Remote Sensing) analysis, and visualization one step further?
Everyone around you is talking about deep learning and machine learning but you feel frustrated as you don't know any programming and think that it is not for you?
This course will introduce you to the basics of deep learning and teach you the application of deep learning algorithms (such as convolution neural networks) for ArcGIS Pro and give you the skills necessary to improve your geospatial skills and get great job opportunities. By the end of this course, you will be able to take your own project and find data, manipulate it with deep learning algorithms, and create useful results for your peers, professors, clients, etc. This course is absolutely a must for all who want to learn deep learning but don't know how to start with this challenging subject.
This course is designed to equip you with the basics of machine learning, and its cutting edge part of deep learning (theoretical and practical knowledge) as applied for geospatial analysis, namely Geographic Information Systems (GIS) and Remote Sensing. By the end of the course, you will feel confident and understand the fundamentals of applying Deep Learning algorithms (such as neural networks) in GIS. I will teach you how to use Deep Learning algorithms for such geospatial tasks as object-based image analysis. By the end of this course, you will have a full idea of the ArcGIS Pro workflow for deep learning, understand Deep Learning frameworks used in ArcGIS, learn the basics of parameter selection, and algorithm application for deep learning GIS tasks. On top of that, you will practice GIS by completing an entire geospatial project by exploring the power of Deep Learning for image analysis and GIS problems using ArcGIS Pro.
The course is ideal for professionals such as geographers, programmers, social scientists, geologists, and all other experts who need to use maps in their field and would like to learn more about Machine Learning in GIS.
One important part of the course is the practical exercises. You will be given some precise instructions and datasets to apply Deep Learning algorithms using the ArcGIS Pro software.
Who this course is for:
- The course is ideal for professionals such as geographers, programmers, social scientists, geologists, and all other experts who need to use maps in their field and would like to learn more about geospatial (GIS & Remote Sensing) analysis.
I am a passionate data science expert and educator. I do regular teaching and training all over the world. I have many satisfied students! And now I will be glad if I can teach also you these interesting, highly applied, and exciting topics!
For GIS & Remote Sensing students:
Order of how to take my courses:
Option 1: Take all individual courses that contain more details and more labs in the following order:
1. Get started with GIS & Remote Sensing in QGIS #Beginners
2. Remote Sensing in QGIS: Fundamentals of Image Analysis 2020
3. Core GIS: Land Use and Land Cover & Change Detection in QGIS
4. Machine Learning in GIS: Understand the Theory and Practice
5. Machine Learning in GIS: Land Use/Land Cover Image Analysis
6. Machine Learning in ArcGIS: Map Land Use/ Land Cover in GIS
7. Object-based image analysis & classification in QGIS/ArcGIS
8. ArcGIS: Learn Deep Learning in ArcGIS to advance GIS skills
8. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1
10. Google Earth Engine for Machine Learning & Change Detection
11. QGIS & Google Earth Engine for Environmental Applications
12. Advanced Remote Sensing Analysis in QGIS and on cloud
Option 2: Take my combi-courses that contain summarized information from the above courses, though in fewer details (labs, videos):
1. Geospatial Data Analyses & Remote Sensing: 4 Classes in 1
2. Machine Learning in GIS and Remote Sensing: 5 Courses in 1
3. Google Earth Engine for Big GeoData Analysis: 3 Courses in 1
4. Google Earth Engine for Machine Learning & Change Detection
5. Advanced Remote Sensing Analysis in QGIS and on cloud