Program

AI for Environmental Sustainability

Leveraging AI for a Greener, Sustainable Future

Enroll now for early access of e-LMS

MODE
Online/ e-LMS
TYPE
Self Paced
LEVEL
Advanced
DURATION
8 Weeks

About

This self-paced program explores AI’s role in environmental sustainability, covering state-of-the-art techniques for climate modeling, managing natural resources, and enhancing renewable energy efficiency. Participants will learn to apply AI to real-world environmental issues, driving sustainable practices.

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Aim

To empower PhD scholars and academicians with advanced AI skills to address environmental challenges, focusing on climate modeling, natural resource management, and optimizing renewable energy sources.

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Program Objectives

  • Understand AI applications in environmental monitoring.
  • Develop AI models for climate prediction and analysis.
  • Implement AI solutions for natural resource management.
  • Optimize renewable energy systems using AI.
  • Ensure ethical and regulatory compliance in AI applications.


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Program Structure

  1. Introduction to AI in Environmental Sustainability
  2. Climate Modeling with AI
  3. Natural Resource Management
  4. AI in Renewable Energy Optimization
  5. Environmental Data Analytics
  6. Case Studies in Sustainable AI
  7. Ethical and Regulatory Considerations
  8. Future Trends in AI and Sustainability

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Participant’s Eligibility

Domain: Environmental scientists, AI researchers, data scientists, renewable energy experts, and policy makers.

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Program Outcomes

  • Develop AI-driven solutions for environmental challenges.
  • Apply AI techniques to climate modeling and resource management.
  • Enhance renewable energy systems with AI optimization.
  • Analyze environmental data for sustainable practices.
  • Navigate ethical and regulatory landscapes in environmental AI.

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Fee Structure

Standard Fee:           INR 15,198           USD 258

Discounted Fee:       INR 7599             USD 129

Batches

Spring
Summer

Live

Autumn
Winter

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Certificate

Program Assessment

Certification to this program will be based on the evaluation of following assignment (s)/ examinations:

Exam Weightage
Mid Term Assignments 20 %
Final Online Exam 30 %
Project Report Submission (Includes Mandatory Paper Publication) 50 %

To study the printed/online course material, submit and clear, the mid term assignments, project work/research study (in completion of project work/research study, a final report must be submitted) and the online examination, you are allotted a 1-month period. You will be awarded a certificate, only after successful completion/ and clearance of all the aforesaid assignment(s) and examinations.

Program Deliverables

  • Access to e-LMS
  • Real Time Project for Dissertation
  • Project Guidance
  • Paper Publication Opportunity
  • Self Assessment
  • Final Examination
  • e-Certification
  • e-Marksheet

Future Career Prospects

  • Environmental Data Scientist
  • Climate Analyst
  • Renewable Energy Consultant
  • AI Research Scientist in Sustainability
  • Environmental Policy Advisor
  • Sustainability Program Manager

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Job Opportunities

  • Environmental consulting firms
  • Government agencies
  • Renewable energy companies
  • Research institutions
  • Non-profit organizations focused on sustainability
  • Universities

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Enter the Hall of Fame!

Take your research to the next level!

Publication Opportunity
Potentially earn a place in our coveted Hall of Fame.
Centre of Excellence
Join the esteemed Centre of Excellence.
Networking and Learning
Network with industry leaders, access ongoing learning opportunities.
Hall of Fame
Get your groundbreaking work considered for publication in a prestigious Open Access Journal (worth ₹20,000/USD 1,000).

Achieve excellence and solidify your reputation among the elite!

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Maybe you can take less time on showing the titles of a paper and take some time to describe in a More few words what actually says the paper and what is important as a summary. Also thank you for the provided papers and websites but I think more explaination needs to be done for the coding because not everybody has a good background on it.
Maria Xinari : 01/22/2026 at 8:00 pm

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Unfortunately, many of the topics listed in the programme were not covered during the workshop, More meaning the course was only partially useful. Additionally, some topics required prior knowledge of programming languages, statistics and data analysis, a prerequisite that was not specified in the course requirements. This made it very difficult to follow that part of the workshop. I find this omission highly inappropriate, given that this is a paid workshop.
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