Admission requirements
This course is an elective module for the joint degree MSc Programme on Industrial Ecology. Students must demonstrate basic skills in Python programming, for example, through the successful completion of the course “Earth System Science and Analysis”. An extended version of the course (4413SUAP6Y) is also open to students of the MSc Governance of Sustainability to better prepare them for the joint part of the course.
Description
Industrial ecology relies on the analysis of potentially large datasets from various sources. This course will help students to choose, explore, process, and share datasets. These datasets are often integrated into models, which are a very simplified representation of our world to allow its operationalization for large scales, due to global supply chains, etc. Therefore, it is important to validate models to test their applicability in other contexts (e.g., time or location), and to assess model uncertainties (e.g., due to model choices or uncertainties in the input data).
All these types of analysis will be carried out in Python, a general-purpose and very popular programming language. A programming language like Python can more easily handle large datasets than many other software tools and spreadsheet programmes. It is also highly flexible and can be customized to integrate different industrial ecology methods which otherwise would have to be performed each using a different software tool. In addition, tasks can easily be repeated which saves time, and every step is well documented. This course builds upon and goes beyond the Python skills gained in Earth System Science and Analysis. It includes code optimization, the creation of simple GUIs, and best practices, such as version control, standardized code documentation, and code sharing.
The skills taught in this course are generic and do not focus on a specific type of “sustainability analysis” but will be applied to sustainability-related topics. The analytical, problem-solving, critical-thinking, and programming skills gained in this course are transferable skills, which are in high demand in the job market of industrial ecology and beyond.
Course objectives
The main learning goal is to gain more practice with Python programming. Sustainability analysis is not a learning goal but serves as the application of Python. More specifically, after completing this course, students are able to:
Process unclean data, describe datasets with metadata, and apply fair data principles
Validate and assess uncertainties of models
Test hypotheses and verify the underlying assumptions
Develop clear and efficient code in Python, integrate user interaction, and keep track of versions
Timetable
In MyTimetable, you can find all course and programme schedules, allowing you to create your personal timetable. Activities for which you have enrolled via MyStudyMap will automatically appear in your timetable.
Additionally, you can easily link MyTimetable to a calendar app on your phone, and schedule changes will be automatically updated in your calendar. You can also choose to receive email notifications about schedule changes. You can enable notifications in Settings after logging in.
Questions? Watch the video, read the instructions, or contact the ISSC helpdesk.
Note: Joint Degree students from Leiden/Delft need to combine information from both the Leiden and Delft MyTimetables to see a complete schedule. This video explains how to do it.
Mode of instruction
Lectures and workshops.
Assessment method
Assessment
The performance in this course will be assessed through one big assignment composed of three take-home sub-assignments and one oral presentation, each with different due dates.
Weighing
The final mark for the course is established by (i) determination of the weighted average combined with (ii) additional requirements. (i) The weights are 70% for writing code, 10% for giving peer feedback, 10% for presenting results, and 10% for writing a short reflection. Students pass the course if the average grade is sufficient. (ii) Another smaller assignment and a quiz will not be graded but need to be completed to obtain a grade for this course.
Resit
If a retake is needed, the student will get more time for the same assignment but can at most score a 6.0.
Inspection and feedback
Each assignment part will be graded based on multiple criteria. These sub-grades will also be reported. Some general feedback will be given for all. For more detailed and individual feedback, students can ask for a time slot within a dedicated review session after all examinations and grading are completed.
Reading list
Course materials.
Registration
As a student, you are responsible for enrolling on time through MyStudyMap.
In this short video, you can see step-by-step how to enrol for courses in MyStudyMap.
Extensive information about the operation of MyStudyMap can be found here.
There are two enrolment periods per year:
Enrolment for the fall opens in July
Enrolment for the spring opens in December
See this page for more information about deadlines and enrolling for courses and exams.
Note:
It is mandatory to enrol for all activities of a course that you are going to follow.
Your enrolment is only complete when you submit your course planning in the ‘Ready for enrolment’ tab by clicking ‘Send’.
Not being enrolled for an exam/resit means that you are not allowed to participate in the exam/resit.
Contact
For substantive questions, contact the course coordinator listed in the right information bar.
Remarks
MSc Industrial Ecology students can register for the course and exam via MystudyMap. Other students need to contact the study advisors of the programme via studyadvisor-ie@cml.leidenuniv.nl
Software
Starting from the 2024/2025 academic year, the Faculty of Science will use the software distribution platform Academic Software. Through this platform, you can access the software needed for specific courses in your studies. For some software, your laptop must meet certain system requirements, which will be specified with the software. It is important to install the software before the start of the course. More information about the laptop requirements can be found on the student website.