Introduction to Environmental Analytics using R June 2024 Batch
For 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
Environmental Analytics offers a rich tapestry of techniques for deeper understanding and management of complex natural environments. 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 patterns 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 analyze environmental data using R programming language.
The 5‑day certificate course will help participants to learn the essentials of environmental analytics. It will also provide an 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 the opportunity to present and discuss the utility of environmental analytics in their own work.
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
The course is intended to be delivered only through in-person lecture and hands-on sessions. Lecture will assist in enhancing the knowledge of the basic and advanced statistics including machine learning, geo-computation and time series analysis 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
All interested participants need to fill out the application form. All participants are required to submit a short description of their specific motivation to join the certificate programme.
The course will be offered from June 03 – 07. The five-day training is divided into lectures for conceptual understanding of data analytics and hands-on sessions in R for processing of data. It will end with a final presentation from participants about the utility of data analytics in their work and in the project they would be working on during the workshop.
Course Content
(All sessions will start at 9 AM and end at 4:30 PM)
| Date | Content |
|---|---|
| 03 June 2024 | Introduction to R, Basics of Non-spatial and Spatial Data and Visualisation |
| 04 June 2024 | Simple and Multiple Linear Regression: Environmental Applications in R |
| 05 June 2024 | Visualisation and Modelling of Spatial Data for Environmental Applications using R |
| 06 June 2024 | Time Series Analysis: Monitoring and Forecasting |
| 07 June 2024 | Presentation of Results by the Participants Followed by Group Discussion and Reflection, Written Feedback, and Presentation of Certificates. Closing Session |
Timeline
Last day to apply
Announcement of results
Last day for fee payment
The decision of the evaluation committee will be final.
Certificate of Participation
The participants will be awarded a certificate of participation after successful completion of the 5‑day training.
Course Instructors
This course will be led by professors who have extensive experience in the field of remote sensing and its applications.
Course Faculty
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Ankur Jamwal
Ankur teaches environmental science at Azim Premji University, and specialises in ecotoxicology and ecophysiology. He has over 10 years of experience in research and teaching courses related to aquaculture, animal physiology, and environmental toxicology. Ankur’s research deals with understanding the effects of environmental stress on the physiology of aquatic animals and has experience working in both field and laboratory-based research.
Before joining Azim Premji University, Ankur worked at Dr. Rajendra Prasad Central Agricultural University (RPCAU), Pusa, Bihar for more than four years. Before that, he was a Postdoctoral Scientist at the University of Lethbridge, Canada. He extensively uses R programming in his research and loves to teach and learn more about the applications of R language in science communication.
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Neeti
Neeti teaches sustainability at Azim Premji University, with experience of more than 20 years in the field of data analytics and geospatial technology. Her research focuses on using various statistical techniques and geospatial tools to address questions in the field of forestry, agriculture, and disaster management.
She has been using R for more than a decade for both spatial and non-spatial data analysis. 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)
Fee Structure
| INR 5900 | General |
|---|---|
| INR 1180 | Field Practice Organisation (FPO) associated with Azim Premji Foundation, including Azim Premji University |
Partial fee waivers are available for deserving research scholars.
Accommodation and other logistics
The course fee does not include accommodation. The university can arrange accommodation for 5 days at an additional cost.
- For non-shared rooms – INR 826 per day
- For shared rooms – INR 413 per day
Requests for accommodation must be made at the time of application. Alternatively, participants can make their own arrangements.
All other costs, such as travel to and from Bangalore, local travel, stay, breakfast, lunch and dinner must be borne by participants.
All rates are inclusive of GST and relevant taxes.