📚 Syllabus & Course Curriculum
Environmental Science & Sustainability
Module-by-module breakdown of AI for Climate-Smart Aquaculture, from foundations to a certified capstone project.
Systems
• Pond, cage and recirculating systems and the differing data each affords
• Water quality parameters that drive mortality: oxygen, ammonia, temperature
• Stocking density, feed conversion and the economics that govern decisions
Monitoring
• In-water sensor deployment, biofouling and calibration drift
• Underwater imaging and acoustic biomass estimation
• Data gaps from power and connectivity limits at remote sites
Models
• Dissolved oxygen and water quality forecasting for aeration control
• Growth and biomass modelling to time harvest
• Disease and mortality early warning, and the cost of a missed event
Feeding
• Appetite detection and demand feeding control
• Feed conversion optimisation and effluent load reduction
• Balancing growth rate against welfare and environmental limits
Climate
• Climate risk: warming, hypoxia, salinity shift and extreme events
• Site selection and species choice under projected conditions
• Certification, traceability and market access requirements
Earn government-registered certification in AI for Climate-Smart Aquaculture
e-Certificate and e-Marksheet issued on successful completion.
