MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 23 lectures (2h 15m) | Size: 937.2 MB
Export geospatial Data including rasters and vectors.
Learn machine learning, big data analysis, GIS, remote sensing with Earth Ee Python API and Jupyter Notebook
Students will access and sign up the Google Earth Ee Python API platform
Access satellite data in Earth Ee
Access images and image collections from the Earth Ee cloud data library
Perform cloud masking of various satellite images
Visualize and analyze various satellite data including, MODIS, Sentinel and Landsat
Visualize series images
Run machine learning algorithms using big Earth Observation data
and Install Anaconda and Jupyter Notebook
Basic understanding of GIS and Remote Sensing
Access to the Google Earth Ee API
Do you want to access satellite sensors using Earth Ee Python API and Jupyter Notebook?
Do you want to learn the spatial data science on the cloud?
Do you want to become a spatial data scientist?
Enroll in my new course to Spatial Data Analysis with Earth Ee Ee Python API.
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 Ee Python API.
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 Ee Python API course, I will help you get up and running on the Earth Ee Python API and Jupyter Notebook. By the end of this course, you will have access to all example script and data such that you will be able to accessing, ing, visualizing big data, and extracting information.
In this course we will cover the following topics:
Introduction to Earth Ee Python API
Install the Anaconda and Jupyter Notebook
Set Up a Python Environment
Raster Data Visualization
Vector Data Visualization
Load Landsat Satellite Data
Cloud Masking Algorithm
Export images and videos
Process image collections
Machine Learning Algorithms
Advanced digital image processing
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 Ee Python API and Jupyter Notebook. All sample data and script will be provided to you as an added bonus throughout the course.
Jump in right now and enroll.
Dr. Alemayehu Midekisa, PhD
This course is meant for professionals who want to harness the power Google Earth Ee Python API and Jupyter Notebook
People who want to understand various satellite image processing techniques using Python and Jupyter Notebook
Anyone who wants to learn accessing and extracting information from Earth Observation data
Anyone who wants to apply for a spatial data scientist job position