This course offers an introduction to using data-driven methods for corporate sustainability challenges. Students will first cover the fundamentals of data analysis project design, including scoping, data sourcing, and ethical considerations. Subsequently, the course is organized into modules covering core analytical techniques, machine learning for prediction, and emerging AI technologies.
Topics:
Exam info and full course description can be found in the course catalogue.
Requirements for taking the exam
In order to participate in the exam, there is an 11 days attendance requirement
Course specific:
To apply for the course you must either be enrolled in a bachelor's degree, have a bachelor's degree or have passed a qualifying entry examination.
To get the most out of this course, we recommend you have some familiarity with the following areas: Introductory statistics, basic coding experience and familiarity with strategy, marketing, finance, or operations management.
General:
Exchange students: nomination from your home university
Freemovers: documentation for English Language proficiency
You can read more about admission here.
