Complete Google Earth Engine with Python API Bootcamp
What you'll learn
- Learn to code Python on the Google Earth Engine Cloud API
- Access and visualize satellite data in Earth Engine Python API
- Access images and image collections from the Earth Engine API
- Apply various machine learning algorithms on the Earth Engine Python API and Colab
- Download, process and visualize various satellite data including Landsat, MODIS, Sentinel and VIIRS
- Apply dpatial analysis techniques to process and analyze various vector data
- Learn to perform various image processing including mosaiccing, compositing, zonal statistics, and neighborhood analysis
- Export images, charts and videos
- Master Python programming language to process Earth observations data
- Apply remote sensing data for forest application
- Apply remote sensing data for drought monitoring
- Apply remote sensing data for crop monitoring
- Apply remote sensing data for flood mapping
Requirements
- This course has no requirements.
Description
Welcome to Complete Google Earth Engine with Python API Bootcamp, the only course you need to learn to code Python and become an Earth Engine cloud computing expert.
Do you want to learn Python and spatial data science on the cloud?
Do you want to become a geospatial data scientist?
At 7+ hours, this course is the most comprehensive Google Earth Engine Python API course available online. Even if you have zero Python programming experience, this course will take you from beginner to mastery.
Here's why:
The course has been updated to be 2024-ready and you'll be learning the latest tools available on the cloud.
The curriculum has just been developed and has the latest technology on the Earth Engine Python API cloud computing
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, 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 Python Api and Google Colab
Explore Earth Engine
Sign Up with Earth Engine
Download Earth Engine Datasets
Creating Charts in Matplotlib
Satellite Spectral Indices (NDVI, EVI)
Mapping Raster Datasets
Mapping Vector Datasets
Working with Images and Image Collections
Digital Image Processing (mosaicing, resampling, convolutions)
Machine Learning
Forest Monitoring
Surface Water Mapping
Humanitarian Applications
Drought Monitoring
Flood Mapping
Crop Monitoring
In this Complete Google Earth Engine with Python Bootcamp course, I will help you get up and running on the Earth Engine Python API and Google Colab. By the end of this course, you will have access to all example scripts and data such that you will be able to access, download, visualize big data, and extract information.
One of the common problems with learning image processing is the high cost of software. In this course, I entirely use open-source software including the Google Earth Engine Python API and Colab. All sample data and scripts will be provided to you as an added bonus throughout the course.
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? Click the buy now button and join.
Who this course is for:
- This course is meant for professionals who want to manipulate big spatial data on the cloud using Earth Engine and Google Colab
- Anyone who wants to learn accessing and extracting information from satellite data
- Anyone who wants to learn accessing and extracting information from satellite data
Instructor
- 4.0 Instructor Rating
- 1,901 Reviews
- 21,626 Students
- 20 Courses
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 to quantify land surface changes including land cover changes, urbanization trends, disease outbreaks, and surface water dynamics.