Vår 2025

PSY-3035 Programming and Data Visualization for Researchers - 10 stp

The course is administrated by

Institutt for psykologi

Type of course

Theoretical.

Aimed at MSc students who will mainly produce quantitative data in their research.

The course can be taken as single course.

Course overlap

HEL-8048 Advanced data analysis and visualization using programming 7 ects

Course contents

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

Local admission, application code 9371 - singular courses.

Objective of the course

Having attended the course and completed the exam the students will obtain the following learning outcomes:

(National Qualifications Framework 1st, 2nd & 3rd cycle)

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

Language of instruction

English

Teaching methods

10 x 3 h seminars/workshops in which students will be presented with mini-lectures and will work on exercises under the supervision of instructors. An additional 6h/week of independent study outside the workshops is recommended.