Data Science in Ecology and Environmental Science (ECSC10038)
Normal Year Taken
Delivery Session Year
Key skillsets in ecological and environmental sciences include quantitative skills such as data manipulation, data visualization, coding, statistics, simulation, and more - together these skillsets can be called data science. With a growing emphasis on the importance of data science in ecological and environmental fields, students are seeking out these quantitative skills for their current academic programmes including dissertation research and future careers. The Data Science in ESS course will promote the development of quantitative skills among honours students (and MSc students when appropriate) using interactive workshops and an online learning platform.
Written Exam 0%, Coursework 100%, Practical Exam 0%
Additional Assessment Information
100% courseworkEngagement via GitHub - maintenance of individual online repository - 20% - 12noon Friday week 11. All work provided in GitHub.Development of a new tutorial- 40% - 12noon Friday week 11. GitHub plus PDF to Turnitin on Learn.Weekly challenges (10% per challenge x 4 challenges) - 40%Challenge 1 set in week 3 - due 12noon Thursday week 5 via GitHubChallenge 2 set in week 5 - due 12noon Thursday week 7 via GitHubChallenge 3 set in week 7 - due 12noon Thursday week 9 via GitHubChallenge 4 set in week 9 - due 12noon Thursday week 11 via GitHub
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