CIS Abroad has joined forces with
CEA CAPA Education Abroad
As part of the CEA CAPA Education Abroad family, you'll find even more opportunities with our expanding global network.
Barcelona SAE has joined forces with
CEA CAPA Education Abroad
As part of the CEA CAPA Education Abroad family, you'll find even more opportunities with our expanding global network.
Practical Case Study: Real-life Modelling in Econometrics and Data Science - Period 3
Business & Economics Program
Amsterdam, Netherlands
Dates: 8/15/26 - 5/29/27
Practical Case Study: Real-life Modelling in Econometrics and Data Science - Period 3
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Economics
Instruction in: English
Course Code: E_MFAE_PCS
Transcript Source: Partner Institution
Course Details: Level 300
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
To participate in this course, students are expected to have followed the courses offered in periods 3.1 and 3.2 of the minor. These provide the foundational tools necessary to engage with any of the case topics. Some cases build directly on material covered in earlier courses, while others introduce more complex methods that require students to explore additional techniques through self-study. The course begins with an introductory lecture that outlines the structure, expectations, and a suggested approach to planning the project.
The focus throughout is on applying methods to real data and interpreting results correctly. Rather than emphasizing technical derivations, the course prioritizes well-reasoned model choices, justification of methodology, interpretation of outcomes, and consideration of alternative approaches. Students are encouraged to think critically, evaluate different modeling strategies, and present their findings in a clear and professional manner. Each case is introduced through a detailed case description and a mandatory kick-off session at the partner's office.
The focus throughout is on applying methods to real data and interpreting results correctly. Rather than emphasizing technical derivations, the course prioritizes well-reasoned model choices, justification of methodology, interpretation of outcomes, and consideration of alternative approaches. Students are encouraged to think critically, evaluate different modeling strategies, and present their findings in a clear and professional manner. Each case is introduced through a detailed case description and a mandatory kick-off session at the partner's office.