2023-2024 / ECON2306-1

Data Management


30h Th

Number of credits

 Master in economics : general (120 ECTS)5 crédits 
 Master in management (120 ECTS)5 crédits 
 Master in business engineering (120 ECTS)5 crédits 
 Extra courses intended for exchange students (Erasmus, ...)5 crédits 


Malka Guillot

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester


Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

This course provides a hands-on introduction to Data Wrangling with the python programming language. You will learn the fundamental skills required to acquire, munge, transform, manipulate, and visualize data in a computing environment that fosters reproducibility.

The focus of the course is mainly applied and aims at directly putting the tools to practice.

Learning outcomes of the learning unit

Upon successfully completing this course, you will be able to:

  • Perform your data analysis in a literate programming environment
  • Manage different types of data
  • Manage different data structures
  • Import, scrape, and export data
  • Index, subset, reshape and transform your data
  • Compute descriptive statistics
  • Visualize data
  • Perform iterative functions
  • Write your own functions
with Python (R and Stata users are welcome, of course).

Prerequisite knowledge and skills

No prior experience is required with any of the software used in class. But you should have already used a statistical or programming software at an introductory level.
Most of all, you should have a taste for coding, collaborating, and looking for answers on the internet.

Planned learning activities and teaching methods

The course mixes interactive lectures and tutorial sessions. Therefore, students must attend the class in person and no broadcast will be possible.

You should plan on bringing your own laptop to class.

  • Lectures: Thursday 13:30-16:30
  • Tutorials: Monday 13:00-14:00

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course

Additional information:

Face-to-face lectures and tutorials. Students are asked to proactively participate during the lectures and tutorials.

Recommended or required readings

All required classroom material will be provided in class or online. Any recommended yet optional material will also be provided in the classroom notes.

Exam(s) in session

Any session

- In-person

oral exam

Written work / report

Continuous assessment

Additional information:

Additional information:

End-term project: written report + oral presentation.

3 problem sets to solve during the term.

Class participation is also important.

Work placement(s)

Organisational remarks and main changes to the course

Website of the 2022 class: https://malkaguillot.github.io/ECON2206-Data-Management-2022/




Professor: Malka Guillot,  mguillot@uliege.be
Assistant: Michel Coppée, Michel.Coppee@uliege.be

Association of one or more MOOCs