Course Description
Give your team a fast, practical tour of how modern farm data platforms turn raw sensor, machinery, and satellite feeds into confident, timely decisions. You’ll see how integrated data lakes and knowledge graphs create a unified view, how predictive and prescriptive analytics drive planning and resource allocation, and how mobile/edge AI brings insights to the field when and where they’re needed.
Who Should Take This Course
Designed for operations managers, agronomists, farm and estate leads, business analysts, product owners in agritech, and consultants supporting agricultural organisations. Ideal for non-technical stakeholders who need to evaluate and apply AI-enabled decision support in day-to-day operations.
Prerequisites
No prior experience needed. Basic familiarity with spreadsheets and data concepts is helpful but not required.
What You Will Learn
- How integrated data lakes and knowledge graphs unify fields, assets, crops, weather, and workflows for a single source of truth.
- Ways to use predictive analytics for operational planning (e.g., yield, labour, input timing) and interpret model confidence.
- How to frame prescriptive AI for resource allocation by translating KPIs into constraints and objectives.
- Design principles for mobile and edge AI that support offline use, low latency, and safe field decisions.
- How to sketch a decision-support blueprint linking data ingestion to action, governance, and ROI tracking.
- Key risks and guardrails: data quality, interoperability, privacy, and MLOps considerations.