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Fundamentals of Modelling and Data Analysis


Admission requirements

This course is obligatory for students of the MSc Industrial Ecology (joint degree Leiden University and TU Delft).
Math skills are expected at high school level.
Prior programming experience is advantageous, but not required.


Industrial ecology relies on models and involves the processing of potentially large datasets.
The language of modelling is mathematics and the tool for data analysis is programming. Both go hand in hand and are essential skills that will help you in your life as an industrial ecologist.
In this course, you will learn to use Python, which is a general-purpose programming language relevant for industrial ecology and beyond. You will need a laptop and Python, which is available for all operating systems. The IDE Spyder is advised, but any alternative is fine as well.

Learning goals

By the end of this course, students should be able to:

  • describe datasets, discuss the importance of data analysis, and explain data transparency principles;

  • apply basic concepts of modelling, evaluate model quality, solve linear algebra problems, and test hypotheses;

  • develop code in a programming language to analyse and visualise datasets.

Teaching methods/mode of instruction

The course will mainly be taught through lectures and exercises. The lectures will introduce new data, modelling, or programming material.
During workshops, students will individually work on exercises – two of them graded assignments – to consolidate their new knowledge, while student assistants will move around the room taking questions.

Type of assessment

60% of the grade will result from an exam, covering the content of the whole course.
40% of the grade will come from two assignments. Each assignment will require the use of a computer.
To pass the course, it is necessary to have a minimum grade of 6/10, as an average of the exam and the two assignments, and a minimum grade of 5/10 in the exam. The students have the opportunity to do a retake of the final exam within the same academic year but not of the assignments.
Final grades are expressed by means of a figure between 1 and 10, rounded to the nearest half. The grade 5.5 cannot be granted. Grades between 5.01 and 5.49 are rounded to 5.0 and grades between 5.50 and 5.99 are rounded to 6.0.
Electronic devices must be switched off during the exam. On the table, you can only have pens and the distributed paper.

Course materials/reading list

The course will use Python3 and the IDE Spyder.
The lecture slides will be provided via Brightspace. For the programming part, the course will follow 'Python for Everybody - Exploring Data Using Python 3' by Charles Severance (2016).


Because this course is part of a joint degree between Leiden University and TU Delft, students (also guest and exchange) have to be enrolled in both universities.
All students have to enrol for the course via Brightspace, TU Delft (before the start of the course) and for the exam via uSis, Leiden University. (see:

Students who are not enrolled for the MSc Industrial Ecology, have to ask for permission from the studyadvisor of Industrial Ecology to join this course, at least one month before the start of the course.

Exchange students can only enroll for this course if their home university has an Exchange agreement with both Leiden University and TU Delft. Exchange students have to ask permission from the studyadvisor of Industrial Ecology as soon as possible, preferably six months before the start of the course.


More information and the description of the course is published in the e-studyguide of TU Delft. The schedule is posted on Brightspace TU Delft.