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HEL-8048 Advanced data analysis and visualization using programming - 10 stp


The course is administrated by

Institutt for psykologi

Type of course

PhD course. This course is available as a singular course.

Course overlap

PSY-3035 Programming and Data Visualization for Researchers 7 ects

Course contents

The course will develop advanced data analysis techniques using programming as a tool and allow candidates to employ sophisticated visualization options. Python and associated packages will be used as a basis. Candidates will master 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 including a thorough understanding of different plot types and how to implement these using code. 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.

A key aspect of the course will involve methods of retrieving datasets from the internet including an introduction to APIs (application programming interfaces). Development of web applications and graphical user interfaces (GUIs) for analysing data will be introduced.

Candidates should have experience analysing and visualizing data including basic statistical training. We recommend that candidates have some prior experience with coding, but it is not a requirement.


Admission requirements

PhD students and students at the Student Research Programme at UiT The Arctic University of Norway register for class and exam in Studentweb by February 1st.

Other applicants apply for the right to study by December 1st, please use UiTs application website.

The following course code must be used:

If granted the right to study, the candidates must register for class and exam in Studentweb by February 1st.

This course has a maximum capacity of 10 candidates. If there are more applicants than available seats, candidates will be given priority from category 1 to 3:

Should we have to make priorities within category 1, students who have gotten the furthest in their course of study, will be given priority.


Objective of the course

Having completed the course the candidates will obtain the following learning outcomes:

Knowledge:

Skills:

General Competence:


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 8h/week of independent study outside the workshops is recommended.