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Complete Google Earth Engine for Remote Sensing & GIS (Udemy.com)

Harness the Power of Google Earth Engine for GIS Spatial Data Analysis & Remote Sensing

Created by: Minerva Singh

Last updated October 2025

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What you will learn

  • Students will gain access to and a thorough knowledge of the Google Earth Engine platform
  • Carry out pre-processing and processing of satellite data in the cloud
  • Implement some of the most common GIS techniques on satellite data
  • Implement time series analysis of multi-temporal optical data
  • Implement machine learning algorithms on satellite data
  • Gain proficiency in JavaScript for satellite data processing

How it compares

Against the other 503 rated Udemy courses in Teaching & Academics on CourseDuck:

  • Rating4.5 out of 5higher than 42% of them
  • Reviews1,591#106 of 504 by number of reviews
  • Length5.6 hourslonger than 67% of them
  • Last updatedOctober 2025more recently than 76% of them

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Course Description

ENROLL IN MY LATEST COURSE ON HOW TO LEARN ALL ABOUT BASIC SATELLITE REMOTE SENSING AND GIS ANALYSIS USING GOOGLE EARTH ENGINE (GEE).

Are you currently enrolled in any of my GIS and remote sensing related courses?

Or perhaps you have prior experience in GIS or tools like R and QGIS?

You don't want to spend 100s and 1000s of dollars on buying commercial software for imagery analysis?

The next step for you is to gain proficiency in satellite remote sensing data analysis and GIS using GEE, a cloud based endeavor by Google that can help process several petra-byte of imagery data

MY COURSE IS A HANDS ON TRAINING WITH REAL REMOTE SENSING AND GIS DATA ANALYSIS WITH GOOGLE EARTH ENGINE- A planetary-scale platform for Earth science data & analysis; powered by Google's cloud infrastructure. !

My course provides a foundation to carry out PRACTICAL, real-life remote sensing and GIS analysis tasks in this powerful cloud-supported paltform . By taking this course, you are taking an important step forward in your GIS journey to become an expert in geospatial analysis.

Why Should You Take My Course?

I am an Oxford University MPhil (Geography and Environment) graduate. I also completed a PhD at Cambridge University (Tropical Ecology and Conservation).

I have several years of experience in analyzing real life spatial remote sensing data from different sources and producing publications for international peer reviewed journals.

In this course, actual satellite remote sensing data such as Landsat from USGS and radar data from JAXA  will be used to give a practical hands-on experience of working with remote sensing and understanding what kind of questions remote  sensing can help us answer.

This course will ensure you learn & put remote sensing data analysis into practice today and increase your proficiency in geospatial analysis.

Remote sensing software tools are very expensive, and their cost can run into thousands of dollars. Instead of shelling out so much money or procuring pirated copies (which puts you at arisk of prosecution), you will learn to carry out some of the most important and common remote sensing analysis tasks using one of the most powerful earth observation data and analysis platform.  GEE is rapidly demonstrating its importance in the geo-spatial sector and improving your skills in GEE will give you an edge over other job applicants..

This is a fairly comprehensive course, i.e. we will focus on learning the most important and widely encountered remote sensing data processing and and GIS analysis techniques in Google Earth Engine

You will also learn about the different sources of remote sensing data there are and how to obtain these FREE OF CHARGE and process them using within GEE.

In addition to all the above, you’ll have MY CONTINUOUS SUPPORT to make sure you get the most value out of your investment!

ENROLL NOW :)

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Instructor Details

Minerva Singh

I completed a PhD (University of Cambridge, UK) in 2017 where I focussed on implementing data science techniques for quantifying the impact of forest loss on tropical ecosystems. I hold an MPhil (School of Geography and Environment) and an MSc (Department of Engineering) from Oxford University. I have more than 10 year's experience in conducting academic research (published in high level peer-reviewed international scientific journals such as PLOS One) and advising both non-governmental and industry stakeholders in data science, deep learning and earth observation (EO) related topics.

I have a strong track record in implementing machine learning, data visualization, spatial data analysis, deep learning and natural language processing tasks using both R and Python. In addition to being educated at the best universities in the world, I have honed my statistical and data analysis skills through many MOOCs, including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R-based Machine Learning course offered by Stanford online) and the IBM Data Science Professional certificate Track. I specialise in a variety of topics ranging from deep learning (Tensorflow, Keras) to machine learning to spatial data analysis (including EO data processing), data visualizations, natural language processing, financial analysis among others. I have acted as a peer reviewer on highly

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Reviews

4.5

1,591 ratings on Udemy

Select a bar to show only those reviews.Select the bar again to show every rating.

By Udemy User on 5/21/2026

not for those who wants to learn from begining. the tutor is teaching herself rather than learners. pathetic lectures

By Elliot Saunders on 5/19/2026

Very informative and beginner-friendly course. The instructor explains concepts step by step and demonstrates how to work with satellite imagery in a practical way. I learned a lot about preprocessing, visualization, and machine learning applications in GEE.

By Adrian Fuller on 5/19/2026

One of the best introductions to Google Earth Engine I’ve found online. The lessons are organized well, and the projects helped me understand how cloud-based geospatial analysis works. I also appreciated the focus on both GIS operations and remote sensing techniques.

By Darren Nichols on 5/19/2026

Excellent course with very practical lessons. I liked how the instructor covered real-world applications such as Landsat processing, image classification, and time series analysis. The explanations are detailed without being overwhelming. Definitely worth taking for anyone interested in GIS and remote sensing.

By Blake Henderson on 5/19/2026

This course exceeded my expectations. The instructor teaches in a clear and structured way, making complex Google Earth Engine and GIS concepts much easier to grasp. I especially enjoyed the practical demonstrations with satellite imagery and remote sensing workflows. Highly recommended for students, researchers, and GIS professionals looking to build real skills.

By Vullgo Darlenny on 2/4/2026

I really enjoyed this course because it combines remote sensing, GIS, and AI in a very structured way. Google Earth Engine can be confusing at first, but the instructor made it easy to follow. The hands-on projects were very useful for building confidence.

By Karlo Alberto E. on 2/4/2026

This course is an excellent resource for anyone interested in remote sensing and GIS using Google Earth Engine. The concepts are explained clearly, starting from the basics and gradually moving to advanced AI-based applications. The practical examples helped me understand real-world use cases very well.

By Chris Pointon on 2/3/2026

The course provided a complete overview of remote sensing and GIS analysis using Google Earth Engine. The coding examples and step-by-step demonstrations made learning much easier. It is perfect for students, researchers, and professionals.

By Avinab Aairaa on 2/3/2026

I found this course extremely helpful for improving my skills in geospatial analysis. The instructor explains complex topics like image classification and time-series analysis in a very understandable way. Highly recommended for beginners and intermediate learners.

By Prity Polly on 3/13/2018

I have never worked with Google earth engine (GEE) before but after working through these lectures I feel more confident. It is a good resource for beginners but it should expand its classification capabilities and include a module on regression too

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Overall Score : 90 / 100