What you'll learn
Students will access and sign up the Google Earth Engine Python API
Access and visualize satellite data in Earth Engine Python API
Export geospatial data including raster and vector data formats
Access images and image collections from the Earth Engine API
Apply various machine learning algorithms on the Earth Engine Python API and Colab
Requirements
Need to have a Google account
Basic understanding of GIS and Remote Sensing
Access to the Google Earth Engine API
Description
Do you want to access satellite sensors using Earth Engine Python API and Google Colab?

Do you want to learn the spatial data science on the cloud?

Do you want to become a geospatial data scientist?

Enroll in my new course to Spatial Data Analysis with Earth Engine Python API and Colab.

I will provide you with hands-on training with example data, sample scripts, and real-world applications. By taking this course, you be able to install Anaconda and Jupyter Notebook. Then, you will have access to satellite data using the Earth Engine Python API and Google Colab.

What makes me qualified to teach you?

I am Dr. Alemayehu Midekisa, PhD. I am a geospatial data scientist, instructor and author. I have over 15 plus years of experience in processing and analyzing real big Earth observation data from various sources including Landsat, MODIS, Sentinel-2, SRTM and other remote sensing products. I am also the recipient of one the prestigious NASA Earth and Space Science Fellowship. I teach over 10,000 students on Udemy.

In this Spatial Data Analysis with Earth Engine Python API and Colab 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 script and data such that you will be able to accessing, downloading, visualizing big data, and extracting information.

In this course we will cover the following topics:

Introduction to Earth Engine Python API and Colab

Set Up a Google Colab Environment

Raster Data Visualization

Vector Data Visualization

Load Landsat Satellite Data

Cloud Masking Algorithm

Calculate NDVI

Export images and videos

Process image collections

Machine Learning Algorithms

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 script will be provided to you as an added bonus throughout the course.

Jump in right now and enroll.

Best,

Dr. Alemayehu Midekisa, PhD

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 apply for a spatial data scientist job position

Screenshots

Citación :

https://rapidgator.net/file/faace093d404a700f942df8bad5ebfd6/mrp8x.Spatial.Data.Analysis.with.Earth.Engine.Python.and.Colab.Update.part1.rar.html
https://rapidgator.net/file/8cf754e0c001d97da4319cab8ba99c6b/mrp8x.Spatial.Data.Analysis.with.Earth.Engine.Python.and.Colab.Update.part2.rar.html


https://uploadgig.com/file/download/a63a4A70c9a62b7d/mrp8x.Spatial.Data.Analysis.with.Earth.Engine.Python.and.Colab.Update.part1.rar
https://uploadgig.com/file/download/8E1b5b0b68A6C757/mrp8x.Spatial.Data.Analysis.with.Earth.Engine.Python.and.Colab.Update.part2.rar


https://nitroflare.com/view/6F0491AFCBD1298/mrp8x.Spatial.Data.Analysis.with.Earth.Engine.Python.and.Colab.Update.part1.rar
https://nitroflare.com/view/E6C0DA607D5C2CD/mrp8x.Spatial.Data.Analysis.with.Earth.Engine.Python.and.Colab.Update.part2.rar