Tips & Tricks

🚀 1. Think Like a Problem-Solver, Not a Note-Taker

This course uses challenge-based learning where you solve real agricultural problems in collaboration with farmers and stakeholders. Early in the semester, create a shared team document to track problem definitions and evolving insights.

📅 2. Follow the Weekly Rhythm

Lectures → weekly coding labs → project meetings. Dodona assignments are due every Monday at 24:00. Set reminders and avoid last-minute work.

💡 3. Coding: Small Bursts Beat Sprints

Your individual grade = group project grade × percentage of assignments you complete × coding exam. Submit early, refine often, and test code on small inputs before using real farm datasets.

👩‍🌾 4. Prepare for Farmer Meetings Like a Consultant

Before meeting farmers, prepare three question types: * Clarifying questions * Data-oriented questions * Impact-oriented questions

🧹 5. Data Governance & FAIR Principles Matter

Your project fails automatically if you ignore FAIR principles. Create a shared checklist covering naming conventions, documentation, and file structure.

📊 6. Visualize Before You Model

Generate key visuals (missing data, histograms, time series, scatter matrices) before applying algorithms.

🤝 7. Take Weekly Project Meetings Seriously

Arrive prepared with one question, one update, and one risk. This dramatically reduces last-minute chaos.

🧭 8. Scope Your Project Ruthlessly

Create a “Not Doing” list by Week 3 to keep your project realistic and implementable.

🎤 9. Present for Stakeholders, Not Teachers

Translate technical results into statements like: * “This helps you decide…” * “This reduces risk by…”

📝 10. Practice Strong Academic Integrity

Document all external assistance, including AI tools, and cite everything properly.