Discover how
data analytics can transform agriculture
to be rewarded for
nutritional outcomes

About the Vitagri Academy

Data Agronomy is a free, 16-module course that teaches you to build, evaluate, and trust predictive models for nutrient-dense food production. You start with statistics and end with forecasts that real farms can act on — six Foundation modules to get your bearings, ten Advanced modules to make you fluent.

The curriculum

Two carrots from the same field can differ in antioxidants by a factor of two hundred.

That gap is the subject of this course. Each module pulls one thread — soil biology, mycorrhizae, near-infrared spectroscopy, statistical modelling — and ties it back to the same question: what, exactly, makes one carrot more nourishing than the next?

Who it's for

Built for practitioners, not classrooms.

If you grow food, advise people who do, or set the rules that shape what they grow, this course is yours. No statistics background required for the Foundation level. The Advanced level assumes you finished the Foundation — and nothing more.

How it works

Read. Try. Be tested. Earn the title.

Each module pairs short editorial reading with one interactive exercise and a graded quiz. Finish the six Foundation modules and you earn the Foundation Certificate in Data Agronomy. Finish all ten Advanced modules and you carry the title Certified Data Agronomist — the first formal credential in the field.

The 16 modules

What Data Agronomy covers.

Modules span soil biology, mycorrhizal networks, the 200-fold antioxidant variation within the same crop type, regenerative practice, near-infrared spectroscopy, and the statistical modelling that connects farming systems to health outcomes — each drawn from Vitagri's Growing Health white paper and over 16,000+ peer-reviewed studies.

Foundation — six modules, earning the Foundation Certificate in Data Agronomy:

  1. Foundations — Before You Begin
  2. What Is a Predictive Model?
  3. The Data We Work With
  4. Statistics Foundations
  5. Introduction to Machine Learning
  6. Inspiration For a Healthier Farming Future

Advanced — ten modules, earning the title Certified Data Agronomist:

  1. Generalised Linear Mixed Models (GLMM)
  2. Ensemble Methods: XGBoost & Random Forest
  3. Metabolomics & Microbial Data
  4. Model Evaluation & Validation
  5. The Bidirectional Architecture
  6. From Theory to Practice
  7. Forecasting — Reading the Future of a Series
  8. Classical Forecasting — Smoothing and ARIMA
  9. Machine-Learning Forecasting
  10. Evaluating and Applying Forecasts