Print Syllabus

Syllabus

P000171 Introduction to Machine Learning in Agricultural Economics, 3.5 Credits

Subjects

Education cycle

Postgraduate level

Grading scale

Language

English

Prior knowledge

Ongoing PhD studies in social sciences/ business studies/ economics (interested students in related fields are subject to agreement). Students should have basic knowledge of programming language (R/ Python). No prior knowledge of ML required.

Objectives

After successfully participating in the course, students will be able to

• Have a general understanding of the possibilities and limitations of Machine Learning and understand core principles as well as difference between ML and Econometrics
• Have a theoretical and applied knowledge of common ML algorithms
• Recognize relevant areas of application and understand differences in applicability across algorithms (No free lunch theorem)
• Understand key evaluation methods and critically assess application cases and outcomes
• Use and apply structured and unstructured data sources, identify relevant data sources

Content

• Key methods in ML and their application: supervised, unsupervised, and deep learning
• Practical applications and recent advances for causal and predictive empirical research
• Data analytics of heterogenous sources of data

Formats and requirements for examination

- Students actively participate in the course and contribute to discussions during the course - Students conceptualize an application case and prepare a short presentation that they will pitch at the end of the course - Students write a course paper that applies methods and good practices introduced in the course - Students submit the script of the data analysis underling the course paper

Additional information

This course is part of the research school People, Society and Sustainability, a joined research school between the Department of Economics and the Department of Urban and Rural Development.

**Preparation**


- Familiarize yourself with R/Python
- Read the papers and the introduction chapters of the books of the literature list
- To be adjusted

Responsible department

Department of Economics