Lecture 1 - Meet + greet

D&D DM-P-DD - Fall 2023

Ass. Prof. Dr. Miel Hostens

Welcome

Meet the teacher

Headshot of Dr. Miel Hostens

Dr Miel Hostens

  • Assistant Professor
  • Sustainable Ruminant Health
  • Department of Population Health Science
  • Find out more at bovi-analytics.com

Meet your teacher, when he was young!

Meet your team partners

  • What is your background in agriculture?

  • What is the main reason to subscribe to the course?

  • What do you really hope to learn?

  • Do you have any coding experience?

Meet the other experts

  • Belen Rabaglino

  • Yara Slegers

  • Hans Vernooij

Digital Agriculture

What is Digital Agriculture

“Digital agriculture refers to the use of digital technologies, information, and communication tools in various aspects of agriculture to enhance productivity, efficiency, and sustainability. This field leverages advancements in technology, such as sensors, automation, data analytics, and connectivity, to collect, analyze, and apply data-driven insights to agricultural practices.

Course learning goals and philosophy

Course learning objectives (part 1)

  1. Understand the fundamentals of digital agriculture and its current challenges.

  2. Explore the various technologies, precision farming techniques and digital tools used in agriculture.

  3. Perform data collection, visualisation, analysis, and interpretation in digital agriculture.

  4. Develop practical skills through hands-on programming activities.

Course learning objectives (part 2)

  1. Explore the applications of artificial intelligence and machine learning in agriculture.

  2. Understand the importance of data privacy and security in digital agriculture.

  3. Evaluate the economic, environmental, and social impacts of digital agriculture.

Topics that will be covered

  • Week 1 - Introduction, programming and team project kick-off
  • Week 2 - Data in agriculture
  • Week 3 - Technologies in agriculture
  • Week 4 - Artificial Intelligence and Machine Learning
  • Week 5 - …

Weekly programming assignment

  • One of the learning goals is to actively stimulate you by weekly programming assignments & assessments

  • We will use the Dodona platform for that. Make sure to try if you have access to the course.

  • Link to the course

Weekly programming assignment

Sign in to Dodona using your Utrecht sign-in

Weekly programming assignment

Subscribe to this course

Weekly programming assignment

Make sure to reach each of the deadlines

Deadline Assignment
Fr, Nov 17th 17:00 R Basics
Fr, Nov 24th 17:00 Programming basics
Fr. Dec 1st 17:00 The tidyverse
Fr, Dec 8th 17:00 Importing Data
Fr, Dec 15th 17:00 TBD

Course overview

Homepage

https://github.com/Bovi-analytics/Digital Agriculture

  • All relevant course materials (and history)
  • Links to Teams, GitHub, Dodona, etc.
  • Let’s take a tour!

Activities: Prepare, Participate, Practice, Perform

  • Prepare: Introduce new content and prepare for lectures by completing the readings
  • Participate: Attend and actively participate in lectures and labs, herd visits
  • Practice: Practice your programming skills
  • Perform: Put together what you’ve learned to analyze real-world data
    • Dodona assignments x 5

Grading

The overall team project score will be multiplied by the % of correctly submitted weekly assignments individually.

Example:

  • Your team project is graded as a group to 16/20

  • You individually submitted 80% correct assignments

  • Your end score is 0.8*16/20 = 12.8/20

Support

  • Office hours
  • Ask (or even better help answering) questions during the course!!!
  • Teams
  • Reserve email for questions on personal matters

Announcements

  • During classes or email
  • If unclear, contact me

Diversity + inclusion

It is my intent that students from all diverse backgrounds and perspectives be well-served by this course, that students’ learning needs be addressed both in and out of class, and that the diversity that the students bring to this class be viewed as a resource, strength and benefit.

  • If you have a name that differs from those that appear in your official records, please let me know!
  • Please let me know your preferred pronouns.
  • If you feel like your performance in the class is being impacted by your experiences outside of class, please don’t hesitate to come and talk with me. I want to be a resource for you.
  • If something was said in class (by me or anyone) that made you feel uncomfortable, please talk to me about it.

Course policies

Team project

  • Team update fridays are supposed to be completed collaboratively.

  • Most of the times we will meet in classrooms at the Martinus G. de Bruin building.

  • Team updates will be at the Future Learning Spaces at the Buys Ballotgebouw; rooms 3.19 or 3.22, unless communicated otherwise.

Academic integrity

To uphold the Utrecht University Code of Conduct:

  • I will not lie, cheat, or steal in my academic endeavors;

  • I will conduct myself honorably in all my endeavors; and

  • I will act if the Code is compromised.

Farm data

  • Be aware that

    • the participating farmers are sharing sometimes sensitive and personal data with you (part of the course).

    • you are supposed to use that data for educational purposes only.

    • your professional conduct is expected.

    • you influence future participation of the collaborating farm(s).

Most importantly!

Ask if you’re not sure if something violates a policy!

Making Digital Agriculture a success

Five tips for success

  1. Help me understanding your needs as well.
  2. Read all the preparation material (if provided) before the lesson begins.
  3. Ask questions and actively collaborate with entire team.
  4. Perform the programming assignments.
  5. Don’t let a week pass by with lingering questions.

This week’s first tasks

  • Get a Dodona account if you don’t have one, you’ll need it for Wednesday first lab.
  • Communicate your Gmail account with m.m.hostens@uu.nl so I can connect you to the Digital Agriculture Google Drive and Google Colab environment.