Programming and Data Visualization for Researchers
About the course
Theoretical.
Aimed at MSc students who will mainly produce quantitative data in their research.
The course can be taken as single course.
The course will introduce programming as a tool for data analysis and visualization using Python and associated packages as a basis. Participants will be given an overview of important concepts in coding and shown how coding can be used to process data and automate tasks, such as the reading and parsing of data files. A significant portion of time will be devoted to data visualization methods. Version control and other tools for project organisation and dissemination will also be covered. The course will focus on Python but key concepts and skills will be applicable to other languages.
Admission requirements
Objectives of the course
Having attended the course and completed the exam the students will obtain the following learning outcomes:
Knowledge and understanding:
- Know how to use basic programming concepts and strategies to solve problems (e.g. code structure, commenting, conditional statements)
- Produce efficient and clean code
- Find and evaluate resources to further skills
- Describe modern initiatives in open science
Skills:
- Use Python and associated data analysis platforms (e.g. Jupyter Notebook, Anaconda, matplotlib) to analyse data
- Initialise and maintain projects using version control (Github)
- Develop and document data analysis pipelines
- Suggest and evaluate different ways of visualizing data
General Competence:
- Develop ways of thinking in a logical and systemic manner
- Document and report analysis projects
Credit reduction
If you pass the examination in this course, you will get an reduction in credits (as stated below), if you previously have passed the following courses:
- HEL-8048 Advanced data analysis and visualization using programming 7 ects
Teaching methods
Language of instruction and examination
EnglishSchedule
The schedules are normally finalized and published well in advance of the start of the semester, often a few weeks beforehand. This gives students the opportunity to organize their studies and prepare for upcoming activities.
It is recommended to check the schedule regularly, as changes may occur.
Examination
| Assignment | Hand in: 14.12.2026 14:00 Hand out: 23.11.2026 09:00 |
Grade: Passed / Not Passed |
To take an examination, the student must have passed the following coursework requirements
| Participation in the seminars and an exercise to test basic Python skills | Grade: Approved – not approved |
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