Programme Parameters
Graduate / Intermediate
3 Weeks (30 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
ML for Ocean Health: Monitoring Marine Ecosystems with AI explores how artificial intelligence and machine learning can transform ocean monitoring and conservation. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
ML for Ocean Health: Monitoring Marine Ecosystems with AI explores how artificial intelligence and machine learning can transform ocean monitoring and conservation.
📋 Course Objectives
1. Put AI Enablement techniques to work on real datasets and case studies.
2. Assemble a documented case study that evidences your applied capability.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in AI Enablement
• R&D engineers and working professionals applying AI Enablement in industry
• Academics and educators building research or teaching capacity in AI Enablement
🚀 Key Learning Outcomes
• A demonstrable AI Enablement 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
Bio‑Indicators & Computer Vision
Develop coral health classification pipelines using hybrid CNN‑SVM models. • Implement real‑time fish species identification and counting with YOLOv10. • Analyze acoustic soundscapes via spectrogram‑based deep learning to separate biophony from anthropophony.
Pollution Tracking & Habitat Stress
Fuse SAR and optical satellite data to detect oil spills and chemical runoff. • Forecast harmful algal blooms with LSTM models using SST and chlorophyll‑a. • Segment mangrove and seagrass habitats to quantify blue‑carbon sequestration.
Conservation Strategy & Policy AI
Design reinforcement‑learning agents to optimize Marine Protected Area boundaries. • Detect illegal fishing activities using AIS trajectory analysis. • Apply XAI (SHAP) to explain priority zones for coastal restoration.
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Python |
| Covered Tool / Platform | TensorFlow |
| Covered Tool / Platform | PyTorch |
| Covered Tool / Platform | Google Colab |
| Covered Tool / Platform | CNN |
| Covered Tool / Platform | SVM |
| Covered Tool / Platform | YOLOv10 |
| Covered Tool / Platform | Spectrogram Analysis |
| Covered Tool / Platform | SAR |
| Covered Tool / Platform | Optical Fusion |
Frequently Asked Questions
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