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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Thank you for the presentations. For future sessions, it would be better if the content were More presented more freely in your own words rather than read from slides. It would also be helpful to demonstrate the R package live during the session.
: 01/02/2026 at 1:39 pm

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really badly prepared, expected much more of this especially when basic programming knowledge is More being required by participants it would be nice to learn something additional and actually discuss the topics that were announced
Franziska Singer : 12/22/2025 at 5:22 pm

Metagenomic Analysis of AMR and HGT

This workshop was really bad. There was no single hands-on component. The mentor was simply reading More through theoretical materials that one can easily get online. She had no sample data to practically illustrate the running of the different tools. AI (Artificial Intelligence) teaches hands-on excellently well and accurately but I wanted to have a human feel of hands-on that’s why I registered for this training.
I sacrificed my Saturday to attend the complimentary class but it is the same repetition. In the third class, there was a consensus that the mentor should come with her fastq file and use that to demonstrate from start to finish how to analyze the data. Is that too hard to do? But no, this Saturday again, she simply went over all of the same theoretical things she put us through during the week. Everyone kept quiet because we got tired of complaining of the same thing.
I am highly disappointed. I did not get value for my hard-earned money. I feel cheated. I feel scammed.

Zainab Ayinla : 12/13/2025 at 9:26 pm

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