autumn 2023
BIO-8032 Advanced course on big data and AI for environmental, ecology and biology science - 5 ECTS
Admission requirements
Who can apply as a singular course student:
- PhD student enrolled at another institution than UiT. PhD students must upload a document from their university stating that there are registered PhD students. This group of applicants does not have to prove English proficiency and are exempt from semester fee.
- Holders of a master´s degree of five years or 3+2 years (or equivalent) may be admitted. These applicants must upload a Master´s Diploma with Diploma Supplement / English translation of the diploma. Applicants from listed countries must document proficiency in English. To find out if this applies to you, see the following list: Proficiency in English must be documented - list of countries. For more information on accepted English proficiency tests and scores, as well as exemptions from the English proficiency tests, please see the following document: Proficiency in english - PhD level studies
Course content
This advanced course is designed to provide PhD students with a comprehensive understanding of the use of big data and artificial intelligence in the fields of environmental, ecological, and biological science. The course coversadvanced topics in data extraction, analytics, and predictive analysis, with a focus on the use of real big data sets relevant to these disciplines (e.g.data used by the students in their research). Students will learn to useGIS programsto analyse spatial big data and createmaps. Additionally, students will learn to design and implement artificial intelligence algorithms to analyse and evaluate big data. The course also delvesinto the ethical considerations surrounding the use of open-access data and the FAIR principles. By the end of the course, students will be well-equipped to apply their knowledge and skills to real-world problems at the intersection of science and society.Objectives of the course
Knowledge:
- Have in-depth knowledge of the concepts and technologies of big data, and how they can be used to inform data-driven decision-making in environmental, ecological, and biological sciences
- Have an advanced understanding of the ethical considerations surrounding the use of open-access data and the FAIR principles.
- Have a thorough understanding of the ethical considerations and best practices for using AI in real-world applications
Skills:
- Utilize advanced techniques for extracting, organizing, and analysing big data, including methods for testing, correlation, clustering, and data visualization
- Have expertise in the use of GIS programs for spatial data analysis of big data
- Design and implement artificial intelligence algorithms to analyse and evaluate big data
General competence:
- Creativity in evaluating, visualizing, and analysing big data, and in writing artificial intelligence algorithms for analysing big data related to environmental, ecological, and biological sciences.
- Apply different learned techniques to real-world data sets and interpret the results to inform data-driven decision making
Examination
| Examination: | Date: | Grade scale: |
|---|---|---|
| Assignment | 06.12.2023 23:59 (Hand in) | Passed / Not Passed |
Coursework requirements:To take an examination, the student must have passed the following coursework requirements: |
||
| Attending group discussions and seminars | Approved – not approved | |
- About the course
- Campus: Tromsø |
- ECTS: 5
- Course code: BIO-8032
- Responsible unit
- Institutt for arktisk og marin biologi
- Spørsmål om emnet
- E-post: ambstudie@hjelp.uit.no
- Kontaktpersoner
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Ingjerd Gauslaa Nilsen
Seniorrådgiver, ph.d.-utdanningen ved BFE-fak
+4777646018
ingjerd.nilsen@uit.no
- Tidligere år og semester for dette emnet