Species Distribution Models with GIS & Machine Learning in R (Udemy.com)

Mapping Habitat Suitability for Conservation Using Machine Learning and GIS in R

( 159 Reviews )

Created by: Minerva Singh

Produced in 2021

What you will learn

You will have a greater clarity of basic spatial data concepts and data types
Carry out practical spatial data analysis tasks in freely available software in R
Analyze spatial data using R

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 96 / 100

Course Description

Are You an Ecologist or Conservationist Interested in Learning GIS and Machine Learning in R?

Are you an ecologist/conservationist looking to carry out habitat suitability mapping?
Are you an ecologist/conservationist looking to get started with R for accessing ecological data and GIS analysis?
Do you want to implement practical machine learning models in R?

Then this course is for you! I will take you on an adventureinto the amazingof field Machine Learning and GIS for ecological modelling. You will learn how to implement species distribution modelling/map suitable habitats for species in R.

My name isMINERVA SINGHand i am an Oxford University MPhil (Geography and Environment) graduate. I finishedaPhD at Cambridge University (Tropical Ecology and Conservation). I have several yearsofexperience in analyzing real life spatial data from different sources and producing publications for international peer reviewed journals.

In this course, actual spatial data from Peninsular Malaysia will be used to give a practical hands-on experience of working with real life spatial data for mapping habitat suitability in conjunction with classical SDM models like MaxEnt and machine learning alternatives such as Random Forests. The underlying motivation for the course is to ensure you can put spatial data and machine learninganalysis into practice today. Start ecological data for your own projects, whatever your skill level andIMPRESSyour potential employers with an actual examples of your GIS and Machine Learning skills in R.

So Many R basedMachine Learning and GISCourses Out There, Why This One?

This is a valid question and the answer is simple. This is the ONLY course on Udemy which will get you implementing some of the most common machine learning algorithms on real ecological data in R. Plus, you will gain exposure to working your way through a common ecological modelling technique- species distribution modelling (SDM) using real life data. Students will also gain exposure to implementing some of the most common Geographic Information Systems (GIS) and spatial data analysis techniques in R. Additionally, students will learn how to access ecological data via R.

You will learn to harness the power of both GIS and Machine Learning in R for ecological modelling.

I have designed this course for anyone who wants to learn the state of the art in Machine learning in a simple and fun way without learning complex math or boring explanations. Yes, even non-ecologists can get started with practical machine learning techniques in R while working their way through real data.

What you willLearn in this Course

This is how the course is structured:

Introduction Introduction to SDMs and mapping habitat suitabilityThe Basics of GIS for Species Distribution Models (SDMs) You will learn some of the most common GIS and data analysis tasks related to SDMs including accessing species presence data via RPre-Processing Raster and Spatial Data for SDMs- Your R based GIS training and will continue and you will earn to perform some of the most common GIS techniques on raster and other spatial dataClassical SDM Techniques- Introduction to the classical models and their implementation in R (MaxENT and Bioclim)Machine Learning Models for Habitat Suitability- Implement and interpret common ML techniques to build habitat suitability maps for the birds of Peninsular Malaysia.

It is apractical, hands-on course, i.
e. we will spend some time dealing with some of the theoretical concepts . However, majority of the course will focus on implementing different techniques on real data and interpret the results. After each video you will learn a new concept or technique which you mayapply to your own projects.

TAKE ACTION TODAY! I will personally support you and ensure your experience with thiscourse is a success.
And for any reason you are unhappy with this course, Udemy has a 30 day Money Back Refund Policy, So no questions asked, no quibble and no Risk to you. You got nothing to lose. Click that enroll button and we'll see you in side the course.
Who this course is for:
AcademicsResearchersConservation managersAnybody who works/will work with spatial data

Time: 3.5h

Instructor Details

Minerva Singh

4.8 Rating
159 Reviews

Hello. I am a PhD graduate from Cambridge University where Ispecializedin Tropical Ecology. I am also a Data Scientist on the side. As a part of my research I have to carry out extensive data analysis, including spatial data analysis.or this purpose I prefer to use a combination of freeware tools- R, QGIS and Python.I do most of my spatial data analysis work using R and QGIS. Apart from being free, these are very powerful tools for data visualization, processing and analysis. I also hold an MPhil degree in Geography and Environment from Oxford University. I have honed my statistical and data analysis skills through a number of MOOCs including The Analytics Edge (R based statistics and machine learning course offered by EdX), Statistical Learning (R based Machine Learning course offered by Standford online). In addition to spatial data analysis, I am also proficient in statistical analysis, machine learning and data mining. I also enjoy general programming, data visualizationand web development. In addition to being a scientist and number cruncher, I am anavid traveler

Reviews

4.8

159 total reviews

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Write a Review

By Christopher Chen on 11/22/2020

Too many of these commands are obsolete or removed from R. They may also require an API which requires credit card sign up. I've had to find work arounds up to section 4 and it's become too difficult.

By Sujay Panda on 10/24/2020

Outstanding course, I learn a lot from this course.

By Eduardo Guajardo on 10/21/2020

Lo unico que sirve es el codigo, el cual no es dificil de obtener en otros lados.

By Ramesh Jadhav on 10/19/2020

The instructor has extensive knowledge about the species distribution models with GIS and Machine learning in R. Her delivery technique through the lectures is perfect. Very useful course for me.

By Gregory Luna Golya on 10/14/2020

Nice workflow. Moving quickly. Not sure if the code will work for R version 4.0.2.

By Irwan Lovadi on 9/27/2020

A very good resource to learn about SDM. The instructor did a great job in delivering lectures. It is important to check Q&A section as it may provide solutions for any issues in running the codes.

By Kaushal on 9/23/2020

Informative and outstanding

By Anonymized User on 9/21/2020

Species distribution model with GIS and Machine Learning in R are perfect examples of applicability of latest methods and technology and the instructor has brought them out very well in the course.

By Mariana Dos Santos Toledo Busarello on 9/14/2020

I really liked it and I learned a lot, I just feel that sometimes there's a discontinuity between the lessons. Since I'm already familiar with R I could fill in the gaps by myself so it wasn't a problem, however I think that people who are unfamiliar with it could end up getting stuck on some parts. The Machine Learning part was amazing and I was surprised by how simple Minerva makes it seem, I look forward to implementing it in my future projects.

By MD RAFIKUL ISLAM on 8/4/2020

If you want to learn about species distribution modeling in R, then this is a very good course. In my point of view, it could be more real project-based rather than having just examples.

By Shiekh Hasina on 7/24/2020

This is my first ever online course which I have completed. I had never thought learning GIS would be this easy and fun. Really enjoyed the course.

By Yaminul islam on 7/24/2020

Wonderful instructor. Easy to follow along. Course is extremely flexible. I have learned the basic skills of species distribution model using GIS software which are gonna very helpful in my future career.