Data Science for Chemistry

Course manual 2025/2026

Course content

This course is built for BSc of Chemistry at the University of Amsterdam (UvA). In this course, the students learn the basics of julia language programming. Additionally, they will learn how to explore multi-dimensional data (e.g. LC-MS or DOSY-IR data) from simple visualization to curve fitting. The following topics will be treated during this course.

1. Introduction to julia programming
2. Julia syntax
3. Data visualization I
4. Data visualization II
5. Matrix algebra & SVD
6. SVD & PCA
7. Data manipulation
8. Data exploration
9. Numerical root finding
10. Numerical integration
11. Curve fitting - Least square

Objectives

• The student is able to explain the mathematical basis for numerical analysis.
• The student is able to analyze mathematical concepts using a high-level programming language.
• The student is able to interpret multi-dimensional datasets.
• The student is able to select an appropriate data processing workflow specific to a given dataset.
• The student is able to apply programming logic to solve chemical problems.
• The student is able to apply the acquired processing tools to chemical datasets.

Learning activities

Attendance

Programme's requirements concerning attendance (OER-B):

• Active participation is expected of each student in the course for which he is registered.
• If a student cannot attend an obligatory part of a programme's component due to circumstances beyond his control, he must report in writing to the teacher in question as soon as possible. The teacher, if necessary after consulting the study adviser, may decide to issue the student a replacing assignment.
• It is not allowed to miss obligatory parts of the programme's component if there is no case of circumstances beyond one's control.
• In case of participating qualitatively or quantitatively insufficiently, the examiner can expel a student from further participation in the programme's component or a part of that component. Conditions for sufficient participation are fixed in advance in the study guide and/or on Canvas.

Assessment

50% of the final grade is coming from a group project. The students will need to get at least 5 for their project grade to be considered.

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Contact information

Coordinator

• dr. S. Samanipour