Environmental Data Analytics using R
Environmental Analytics offers a rich tapestry of techniques for a deeper understanding and management of the complex natural environment. The studies on different facets and processes of the environment are increasingly data-rich with the great need of applying various advanced techniques to uncover and extract hidden meaningful pattern that could be of assistance in sustainable environmental management.
The course aims to provide basic understanding of statistics and machine learning approaches with extensive hands-on training to analyse environmental data using R programming language.
The 5‑day certificate course will help participants to learn the essentials of environmental analytics. It will also give opportunity to learn about various applications of statistical approaches including machine learning algorithms in the field of environmental and climate science. With extensive hands-on training using R, participants will learn about different insights one can extract from the data. At the end, participants will have opportunity to present and discuss utility of environmental analytics in their own work.
The course is intended to be delivered through lecture and hands-on sessions. Lecture will assist in enhancing the knowledge of the basic and advanced statistics including machine learning, while hands-on tutorial will give exposure to how to use the R for analysing environmental data.
On successful completion of the course, participants will:
Get familiar with R programming language
Perform environmental data analysis using R
Apply various algorithms for extracting information from environmental datasets
Visualise datasets and outputs in R
Participants from NGOs, academicians, early career researchers and PhD scholars working in the field of environmental science and allied sectors with basic knowledge of statistics
All interested participants need to fill the application form. All the participants are required to submit their specific interest in joining the certificate programme. This should be done using apply button at the beginning of this page.
For any queries, please write to environment.workshop@apu.edu.in
Course Faculty
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Neeti
Neeti is a scientist with experience of more than 20 years in the field of data analytics and geospatial technology. Her research focuses on using various AI-based approaches and geospatial technology in the field of forestry, agriculture, and disaster management.
Before joining Azim Premji University, she worked at Indian Space Research Organisation (ISRO), Clark University, Goddard Space Flight Centre, Boston University, Woods Hole Research Centre (WHRC), and TERI School of Advanced Studies (TERI SAS).
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Kedar Kulkarni
Kedar teaches courses in climate change, statistics and R programming at the University. His research interests lie at the nexus of agricultural economics, environmental economics and development economics.
He holds a PhD in Applied Economics from Oregon State University, USA, a Master’s in Quantitative Economics from the University of Paris Pantheon-Sorbonne, France, and a BA in Economics from the University of Hyderabad, India.