Teaching
Most of our teaching takes place in the M.Sc. Digital Farming (M-DF, hswt.de/mdf), an English-taught programme that combines agricultural sciences with data science, robotics, and AI.
Prof. Dr. Florian Haselbeck is the programme director of M-DF and, together with the team, covers its core methodological modules from first programming steps to applied research projects using AI and robotics.
We also contribute AI modules to other HSWT programmes at Bachelor and Master level.
Winter Term
- Foundations of programming (M-DF, 1. Sem.): Python programming skills from scratch for new M-DF students.
- Artificial intelligence 2 (M-DF, 3. Sem.): advanced deep learning methods and their application to agricultural data.
- Seminar digital farming (M-DF): pairs of students work on a current research topic for one semester, presenting their results in a poster session and supplemented by two-weekly presentations from industry and research partners. Offered in each term and coordinated by us in the winter terms.
- Project applied digital farming (M-DF, 3. Sem.): groups of three to four students spend a semester on an applied project in the context of digital farming, to which we contribute supervising multiple teams.
- KI im Agribusiness (M.Sc. Agrarmanagement): classical machine learning methods and use cases along the agricultural value chain in an hands-on course.
- Blockkurs Python Programmierung (Bachelor elective): compact introduction to basic programming in Python.
Summer Term
- Artificial intelligence 1 (M-DF, 2. Sem.): foundations of machine learning with a focus on classical supervised algorithms.
- Agricultural robotics (M-DF, 2. Sem.): field robotics and autonomous machinery, to which we contribute the software parts.
- Precision livestock farming (M-DF, 2. Sem.): applications of digital technologies in livestock farming, to which we contribute the AI-based approaches.
- Einführung in KI (Bachelor elective): introduction to basic AI concepts and their implications for agricultural Bachelor students.
Thesis Supervision
In addition to coursework, our team actively supervises Bachelor’s and Master’s theses. We welcome motivated students to join our lab for their final projects, whether by applying to our ongoing research topics or proposing their own ideas in the fields of AI, robotics, and digital farming. Visit our Open Positions page to view current thesis opportunities and a list of previously supervised topics.