📚 Syllabus & Course Curriculum
Data Science & Analytics
Module-by-module breakdown of Food Personalization through Data Analytics and AI, from foundations to a certified capstone project.
Nutrition Science
• Dietary assessment methods and their substantial measurement error
• Nutrigenomics evidence and the gap between marketing and science
• Glycaemic response variability and what the published trials actually showed
Data
• Food logging, image-based estimation and systematic under-reporting
• Continuous glucose monitoring and wearable-derived signals
• Microbiome profiling and the current limits of dietary inference from it
Modelling
• Personalised response prediction and the strength of the evidence
• Recommendation systems constrained by nutritional adequacy
• Avoiding recommendations that are optimal numerically and harmful practically
Products
• Personalised product formulation and manufacturing constraints
• Supply chain and cost realities of individualised nutrition
• Labelling, claims regulation and permissible health claims
Ethics
• Evaluating commercial personalisation claims critically
• Risk of promoting disordered relationships with food
• Data protection for health and dietary data
Earn government-registered certification in Food Personalization through Data Analytics and AI
e-Certificate and e-Marksheet issued on successful completion.
