Unlock your GIS skills with our practical course on spatial data analysis using R, QGIS, GRASS, and Google Earth. Learn to impress future employers!
Dive into this hands-on GIS course, where you'll learn advanced spatial data analysis techniques using R, QGIS, and GRASS. Perfect for intermediate users wanting to impress employers!
Become an Open source GIS Guru and Tackle Spatial Data Analysis Using R, QGIS, GRASS & GOOGLE EARTH
PRACTICAL TRAINING WITH REAL SPATIAL DATA FROM DIFFERENT SOURCES.
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DEVELOP MAD GIS SKILLS AND PERFORM SPATIAL DATA ANALYSIS USING FREE KICKASS TOOLS SUCH AS QGIS, R, GRASS AND GOOGLE EARTH.
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This course is designed to take users who use R and QGIS for basic spatial data/GIS analysis to perform more advanced GIS tasks (including automated workflows and geo-referencing) using a variety of different data. In addition to making you proficient in R and QGIS for spatial data analysis, you will be introduced to another powerful free GIS software.. GRASS.
This course takes a completely practical approach to spatial data analysis and mapping- Each lecture will teach you a practical application/processing technique which you can apply easily.
The course is taught by Minerva Singh, A PhD graduate from Cambridge University, UK, who has several years of research experience in Quantitative Ecology and an MPhil in Geography and Environment from Oxford University. Minerva has published papers in international peer reviewed journals and given talks at international conferences.
The underlying motivation for the course is to ensure you can put spatial data analysis into practice today and develop sound GIS analysis skills. You’ll be able to start analyzing spatial data for your own projects, and IMPRESS YOUR FUTURE EMPLOYERS with examples of your PRACTICAL spatial data analysis abilities. This course is different from other training resources. Each lecture seeks to enhance your GIS skills in a demonstrable and tangible manner and provide you with practically implementable GIS solutions.
This is an intermediate course in spatial data analysis, i.e. we will build on on basic spatial data analysis tasks (such as those covered in the beginner version course: Core Spatial Data Analysis: Introductory GIS with R and QGIS) and teach users how to practically implement more complex GIS tasks such as interpolation, mapping spatial data, geo-referencing and detailed vector processing. Additionally you will be introduced to preliminary geo-statistics and mapping/visualizing spatial data.
This course covers complex GIS techniques, and by completing this course, you will be implementing these PRACTICALLY in freely-available software, thus making you MORE ATTRACTIVE TO EMPLOYERS.
It is a practical, hands-on course, i.e. we will spend a tiny amount of time dealing with some of the theoretical concepts pertaining to the different spatial data analysis techniques demonstrated in the course. However, majority of the course will focus on working with real spatial data from different sources. After each video you will learn how to practically implement a new concept or technique in the different softwares used for the course.
During the course of my research I have discovered that R is a powerful tool for collating and analyzing spatial data acquired from different sources. Proficiency in spatial data analysis in R and QGIS has helped me publish more peer reviewed papers faster. Feel free to check out my profile on ResearchGate.
FREE BONUS: You will have access to all the data used in the course, along with the R code files. You will also have access to future lectures, resources and R code files. Enroll in the course today & take advantage of this special bonus!
I don’t have to remind you that we have a RISK-FREE GUARANTEE in the case of you not being satisfied with the course. Take action now!
Carry out the most common spatial data analysis and GIS tasks using free software tools
Perform advanced spatial data analysis and mapping using both R and QGIS
Develop robust map-making skills including harnessing the power of Google Earth.
5 Lectures
7 Lectures
12 Lectures
11 Lectures
10 Lectures
7 Lectures
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...
Lectures resources and key code (libraries) related with spatial analysis using r, is obsolete. Thats makes r examples broken. Libraries as rgeos, maptools, and other are not used any more. Many gfunctions as gBuffer, etc no longer available. The code have to be updated with SF libraries code. readShapeFilePoly is now st_read and so on. This happen to many R Spatial Analysis courses not updated after 2023. It is a matter of maybe create a guide or update code files (not the videos as will be lot of work). Excellent instructor. QGIS examples are ok.
A good open-source GIS course
A very good GIS course in R and QGIS
This course was a good match for me because I love playing with Google Maps during my free time!
Course is outdated
I like how clear it is to follow along
This is an amazing course, but the R lessons are old, and most of the codes and packages are not supported in the latest version of R. That makes it difficult to practice with.
The course is beyond my expectations as it contains valuable information which has immense practical value.
This is an ideal course for studying the utility and importance of various tools for spatial data analysis.
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Bapan S.
outstanding 😍