AI for Food Safety and Quality Control

AI for Food Safety and Quality Control
AI for Food Safety and Quality Control

Course Description

This micro-course shows how artificial intelligence can strengthen food safety and quality control across the production line—from camera-based grading and sorting to predictive microbiology, traceability, and spoilage detection. You’ll learn where AI adds measurable value, what data and governance are required, and how to pilot solutions that align with existing compliance frameworks.

Who Should Take This Course

Ideal for quality assurance and food safety managers, operations leaders, production supervisors, R&D/food technologists, supply-chain and procurement teams, and compliance/regulatory professionals. Consultants and IT/data partners supporting food manufacturers, processors, or retailers will also benefit.

Prerequisites

No prior experience needed. Familiarity with HACCP or similar food safety programs is helpful but optional.

What You Will Learn

  • Identify high-impact AI use cases in inspection, grading, and sorting with vision systems
  • Interpret microbial risk prediction outputs to inform preventive controls and testing plans
  • Map end-to-end traceability using blockchain plus AI for anomaly detection and recall readiness
  • Detect early signs of spoilage using sensor data, imaging, and time-series models
  • Define data, people, and process requirements, including KPIs and validation criteria
  • Assess build-vs-buy options, vendor due diligence questions, and ROI/risk trade-offs

Course Content

AIW-0107-AGR-02: AI for Food Safety and Quality Control
AIW-0107-AGR-03: AI Vision Systems for Grading and Sorting
AIW-0107-AGR-04: Microbial Risk Prediction Models
AIW-0107-AGR-05: Traceability Using Blockchain and AI
AIW-0107-AGR-06: Early Detection of Spoilage
AIW-0107-AGR-07: Conclusion
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