Big Data and Artificial Intelligence for Environmental, Ecological and Biological Science: An Introduction

The “Big Data and Artificial Intelligence for Environmental, Ecological and Biological Science: An Introduction” course, coded BIO-3032, unfolds in a structured, multi-faceted approach to facilitate a profound understanding of Big Data and AI, emphasizing their pivotal roles in ecological and biological sciences. It encompasses 10 ECTS, translating to a comprehensive 300 hours of student engagement across various learning modalities, thoughtfully designed to cater to diverse learning preferences and promote an inclusive educational environment.

Provided by: UiT The Arctic University of Norway

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The course provides an introduction to Big Data and AI, focusing on data extraction, analysis, and predictive analysis. Students will learn about different data formats and techniques for converting data, as well as testing, correlation, clustering, and data visualization. The course covers open-access data and FAIR principles and uses real-world big data sets related to environmental, ecological and biological sciences. Students will create AI algorithms to analyze big data. The course emphasizes collaboration and group work, preparing students for careers at the intersection of science and society.

Venue

Tromsø University, Tromsø & Online

Deep tech fields

Artificial Intelligence & Machine Learning (including Big Data)

Country

Norway

Course language

English

Fee

Free course

Duration (hours)

300

Certificate provided

Yes

Skills addressed

Analyse big data; Data mining; Principles of artificial intelligence; Algorithms; Python (computer programming); Data visualisation; Sustainability analytics

Course format

Hybrid

Target group

Postgraduate-level learners

Quality check

Approved

Current no dates scheduled

UiT The Arctic University of Norway

Situated at the frontier of the Arctic, UiT The Arctic University of Norway proudly stands as the northernmost university in the world. This unique location does not merely represent a geographical d..

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