Level up your traditional geospatial skills by harnessing the power of Google Earth Engine cloud computing and big data
Welcome to the Google Earth Engine Mega Course: Remote Sensing Applications, the only course you need to learn to code and become an Earth Engine expert. With a 4.5 average rating, this Earth Engine course is one of the highest-rated courses.
At 12+ hours, this Earth Engine course is without a doubt the most comprehensive Google Earth Engine course available online. Even if you have zero programming experience, this course will take you from beginner to mastery.
Here's why:
The course is taught by an experienced geospatial data scientist.
The course has been updated to be 2024-ready and you'll be learning the latest tools available on the cloud.
The curriculum was developed over five years, with comprehensive student testing and feedback.
We've taught over 20,000 students how to code and apply spatial data science and cloud computing.
The course is constantly updated with new content, with new projects, and modules.
You will have access to example data and sample scripts.
In this course, we will cover the following topics:
Introduction to Earth Engine JavaScript API
Explore Earth Engine
Sign Up with Earth Engine
Basic JavaScript Data Types
Earth Engine Objects
Client versus Server Side Objects
Image Visualization
Filtering Image Collection
Feature Collection
Clipping Images
Import and Export Images
Cloud Masking
Calculate Spectral Indices
Reducers
Zonal Statistics
Machine Learning Classification
Drought Monitoring
Urban Mapping
Surface Water Mapping
Forest Monitoring
Air Pollution Monitoring
Earth Engine Web Apps
The course includes over 12+ hours of HD video tutorials. We'll take you step-by-step through engaging video tutorials and teach you everything you need to know to succeed as a spatial data scientist and Earth Engine expert.
So, what are you waiting for? Enroll now and start learning!
Students will access and sign up the Google Earth Engine platform
Download, process and visualize various satellite data including Landsat, MODIS, Sentinel and VIIRS
Apply GIS techniques to process and analyze various vector data
1 Lectures
1 Lectures
1 Lectures
5 Lectures
7 Lectures
4 Lectures
6 Lectures
2 Lectures
5 Lectures
5 Lectures
4 Lectures
5 Lectures
1 Lectures
1 Lectures
Dr. Alemayehu Midekisa is a geospatial data scientist with over 15 years of professional experience in academia and industry. His research focus is on leveraging geospatial AI, big Earth observation data, and cloud computing to monitor environmental changes. Dr. Midekisa is particularly interested in applying machine learning models, large-scale remote sensing data, and cloud computing such as Google Earth Engine...
Spatial eLearning provides online courses teaching remote sensing, GIS, machine learning, cloud computing, and spatial data science skills. Our mission is to make highly valuable geospatial data science skills accessible and affordable to anyone and anywhere around the world. We teach 20,000 plus students in over 170 countries around the world. Spatial eLearning’s valuable learning resources include webinars, books, free...
It was super exciting
There was a lot to learn in this course.
Great presentation!
I get best experience study GEE
It is okay. But there is a lot of mumbling and 'um', which can be a little distracting. A little bit of context would be helpful - a 'so what' element. Also, I couldn't get the exercise to work, and there didn't appear to be a solution.But it's okay. I'm learning something.
very bad class
The course is full of technical issues and uses outdated technical resources;
The teacher doesn't fix the errors, despite saying he will (some responses are already from years old).
The course lacks explanations at various moments. As he himself says, they are lectures and not lessons.
In some lectures, besides not sharing the code, it is also not readable on the screen, so you can't complete the code.
When answering questions, it is common not to resolve the doubts or not to have understood them.
Despite all of this, IF you have a solid theoretical foundation, you can benefit, as numerous relevant applications are shown.
I'd like to take this course again if possible. This was extremely intricate to things I've hoped to gain knowledge of.
Great
Your email address will not be published. Required fields are marked *
Emilio P.
Too much time spent explaining very easy stuff.