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

Signals: Milestone gates met; measurable result reported; documentation; deployment or evidence reachable; reflective log

Functionality & requirements30
Technical quality & architecture25
Documentation15
Deployment & evidence15
Innovation10
Presentation5

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.