09-10-2023, 06:21 AM
Species Distribution Models with GIS and Machine Learning in R
Mapping Habitat Suitability for Conservation Using Machine Learning and GIS in R
(506 ratings)
6,157 students
4 hours on-demand video
1 article
26 downloadable resources
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 adventure into the amazing of 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 is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience 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 learning analysis into practice today. Start ecological data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual examples of your GIS and Machine Learning skills in R.
https://www.udemy.com/course/species-distribution-models-with-gis-machine-learning-in-r/?couponCode=FREECOUPNCODE2023A
Enjoy!
Mapping Habitat Suitability for Conservation Using Machine Learning and GIS in R
(506 ratings)
6,157 students
4 hours on-demand video
1 article
26 downloadable resources
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 adventure into the amazing of 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 is MINERVA SINGH and i am an Oxford University MPhil (Geography and Environment) graduate. I finished a PhD at Cambridge University (Tropical Ecology and Conservation). I have several years of experience 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 learning analysis into practice today. Start ecological data for your own projects, whatever your skill level and IMPRESS your potential employers with an actual examples of your GIS and Machine Learning skills in R.
https://www.udemy.com/course/species-distribution-models-with-gis-machine-learning-in-r/?couponCode=FREECOUPNCODE2023A
Enjoy!