MATH5271 is available to Honours, Graduate Diploma and Masters programs in Mathematics, Statistics, Data Science, and Physical Oceanography.
Units of credit: 6
Pre-requisite: 12 units of credit in Level 2 Maths courses including (MATH2501 or MATH2601) and (MATH2801 or MATH2901), or (both MATH2019/8 and MATH2089), or (both MATH2069 and MATH2099) or equivalent. Some computing experience (R, Fortran, Maple, Matlab, and/or Python) is strongly recommended.
Cycle of offering: No offered every year
Graduate attributes: This course is a graduate level overview of the applications of data science in an environmental context. Although applications and motivations will be drawn primarily from the ocean, atmospheric and climate sciences, the material covered will apply generally across various environmental and non-environmental science and industry areas.
A key distinction between this course and other data science offerings within the School of Mathematics and Statistics is an emphasis on practical real-world problems.
More information: The Course outline will be made available closer to the start of term - please visit this website: www.unsw.edu.au/course-outlines
The Course Outline provides information about course objectives, assessment, course materials and the syllabus.
Important additional information as of 2023
The University requires all students to be aware of its policy on plagiarism.
For courses convened by the School of Mathematics and Statistics no assistance using generative AI software is allowed unless specifically referred to in the individual assessment tasks.
If its use is detected in the no assistance case, it will be regarded as serious academic misconduct and subject to the standard penalties, which may include 00FL, suspension and exclusion.
The Online Handbook entry contains information about the course. (The timetable is only up-to-date if the course is being offered this year.)
If you are currently enrolled in MATH5271, you can log into UNSW Moodle for this course.
The course aims to provide a broad overview of Data Science and would provide a platform for further studies in Data Science and an understanding and appreciation of Data Science in the modern world.