Programme Parameters
Advanced Postgrad
3 Days (4.5 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
A 3‑day intensive online course that equips you with the skills to detect, analyze, assess risk, and design circular‑economy interventions for microplastics pollution. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
A 3‑day intensive online course that equips you with the skills to detect, analyze, assess risk, and design circular‑economy interventions for microplastics pollution.
📋 Course Objectives
1. Apply Artificial Intelligence methods to authentic research and industry problems.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A demonstrable Artificial Intelligence project for your research or industry portfolio.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Day 1 – Detection, Characterization & Data Analytics
Explore sources, pathways and environmental fate of micro‑ and nanoplastics • Operate microscopy, FTIR, Raman and AI‑assisted image analysis techniques • Clean and visualize particle‑level datasets in Google Colab using Python libraries
Day 2 – Risk Assessment & Spatial Mapping
Construct risk‑scoring models incorporating size, polymer type and concentration • Apply QGIS and Google Earth Engine to map contamination hotspots • Prioritize high‑risk zones using data‑driven decision frameworks
Day 3 – Mitigation, Circular Economy & Intervention Design
Identify mitigation pathways across product design, wastewater and textile sectors • Run life‑cycle assessments with OpenLCA to evaluate circular alternatives • Design a decision‑matrix dashboard to rank interventions by impact, cost and circularity
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | Python |
| Covered Tool / Platform | Pandas |
| Covered Tool / Platform | NumPy |
| Covered Tool / Platform | Matplotlib |
| Covered Tool / Platform | Scikit-learn |
| Covered Tool / Platform | Plotly |
| Covered Tool / Platform | Streamlit |
| Covered Tool / Platform | OpenRefine |
| Covered Tool / Platform | QGIS |
Programme Faculty & Mentors
Frequently Asked Questions
Scholar Feedback & Reviews
Based on 0 scholar submissions
Rating Breakdown
No verified reviews published yet. Be the first to share your academic experience.
Leave Scholar Feedback
Your rating will help prospective scholars. Ratings below 3 stars are routed privately to the faculty mentor for immediate response.
