Engineers Clinic
IntermediateEngineering trackCA-CP-31

Prairie Grain Yield Prediction from Satellite Data

Internship role: Agri Data Science Intern. Predict canola and wheat yields at the municipality level, validate against Statistics Canada reports and visualise error by region.

10 Guided Steps240h Internship TierSubmit: GitHub repo or evidence pack + live demo / report + README + milestone logbookVerified CertificateAI Rubric Graded
Program Overview

Internship role: Agri Data Science Intern. Predict canola and wheat yields at the municipality level, validate against Statistics Canada reports and visualise error by region.

What you submit

GitHub repo or evidence pack + live demo / report + README + milestone logbook

Stack: Python, Sentinel-2, AAFC crop inventory, LightGBM

How it is graded
  • Problem & requirements15

    Loads, constraints, standards and success criteria are written down before the design starts.

  • Calculations & analysis30

    Hand calculations or simulation set out step by step with units, assumptions and a check against a second method or code limit.

  • Design output20

    Drawings, models, schematics or code that match the calculations and could be handed to the next person.

  • Validation & files15

    Test data, simulation files, calculation sheets or photos attached, with what each one shows.

  • Report & judgement20

    A clear report that states the result, its limits, cost or risk, and what you would change next.

Pass 60% · Merit 75% · Distinction 90%

Learning Outcomes
240-hour Canada programme. Agriculture and Agri-Food Canada and grain companies invest in crop-forecasting analytics.
Target Audience

Engineering Students

Diploma, B.Tech, B.E., BCA, MCA, or M.Tech students seeking practical experience.

Aspiring Developers

Developers who want to build proof-of-work capstone projects for tech resumes.

Job Seekers

Graduates looking for AI-evaluated code review & verified industry credentials.