Week 1

Welcome to Data Science Applications in Agriculture

Introduction

Welcome to Data Science Applications in Agriculture! In this course, we explore how data science, programming, AI, and digital technologies can be applied to real-world agricultural problems and decision-making.

Learning goals

  1. Understand the course structure, expectations, and semester projects

  2. Get to know the instructional team and project topics

  3. Understand the role of data science in agriculture

  4. Set up a programming environment and run basic Python code

Please take a moment to fill in this form so we can tailor the course to your needs: Pre-course questionnaire

Lecture - Course Overview

Introduction to the course, expectations, semester projects, and applications of data science in agriculture.

Lab - Toolbox: IDEs, Programming Languages & Vibe Coding

Introduction to common development tools, including VS Code, Google Colab, Cursor, PyCharm, RStudio, and Claude Cowork.

Students will set up VS Code for Python and run a basic Python program.

Discussion - Data Science in Agriculture

What is data science, and how is it changing agriculture?

Topics include data lineage, satellite data, AI agents, and packages and environment management.

Assignment

Run a provided Python program using one of the IDEs introduced in class and submit a screenshot showing successful execution.

Looking ahead

Next week we will introduce Git and GitHub to help us track, organize, and collaborate on our code and projects.

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