Learning objectives

1. Understand the data science landscape and its applications in agriculture.

2. Develop practical coding skills using Python and modern data science tools.

3. Apply data science workflows and FAIR principles to organize, manage, and analyze agricultural data.

4. Scope agricultural problems using systems thinking and translate them into data science projects.

5. Independently design and execute a data science project, from problem definition to results and communication.

6. Reflect on their learning and take ownership of their development as data science practitioners.

7. Collaborate effectively in teams to solve real-world agricultural problems.

8. Use AI responsibly and efficiently, recognizing its capabilities, limitations, and implications