Type of course

Admission requirements

Higher Education Entrance Qualification (generell studiekompetanse) or prior learning and work experience (realkompetanse).

Application code (Nordic applicants): 9199

Recommended prerequisite: Broad knowledge about fisheries, aquaculture production and the biology related to these industries, e.g. from the FHV, or general biology from a biology programme, is an advantage. Some previous experience in programming languages (e.g. R) and as a user of Linux systems is also an advantage, but it is not required.

Course content

The objective of this course is to give students an understanding of how modern data science tools can be used to solve problems and provide solutions for fisheries, aquaculture, and biology. Practical knowledge and experience with data science tools are key in today’s science, industry, and management and a valuable skill to obtain. The course provides basic training in programming languages (R and BASH) and statistics. The students acquire skills and competence in the use of remote computing environments and online data resources.

The course focuses on illustrating how science, industry, and management can utilize data science to solve problems related to human impact and changing ecosystems. We will also introduce molecular genetics and ecological problems that can be solved with bioinformatics. The course will also include traditional statistical methods used in data science and we will learn ways to visualize results. The use and data mining from open-data platforms, such as BarentsWatch, NCBI Genbank and the BOLD database, will also be covered and used throughout the course to solve relevant problems.

The course is divided into two main modules: Data science and bioinformatics and includes theory and extensive hands-on practical sessions.

Objectives of the course

A candidate who has completed his or her qualification should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge:

The candidate

• understands the foundations of data science and its potential applications in biology, fisheries, and aquaculture
• has broad knowledge of the importance of genetic and biodiversity information for the management of natural ecosystems, fisheries and aquaculture
• has knowledge on organizing and structuring different kinds of data to facilitate the analysis and inferring useful information

Skills:

The candidate

• can write simple scripts to analyze and visualize data
• can retrieve public data from on-line data repositories
• can analyze genetic sequences using bioinformatics tools
• can access remote servers and computing resources

Competence:

The candidate

• can implement data science approaches to solve practical problems
• can apply data science as a leveraging tool to address current societal challenges
• can exchange opinions and experiences with others with a background in the field, thereby contributing to the development of good practice

Language of instruction and examination

Teaching methods

Information to incoming exchange students

This course is available for inbound exchange students.

This course has academic prerequisites. Please see the «Admission requirements» section for more information.

Do you have questions about this module? Please check the following website to contact the course coordinator for exchange students at the faculty: INBOUND STUDENT MOBILITY: COURSE COORDINATORS AT THE FACULTIES | UiT

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