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This course extends multivariate data science techniques to topics such as classification, data fitting, regularization and regression. The focus of this course is on the methods which support many modern data processing applications. Students will be introduced to multivariate statistical techniques, linear algebra and calculus topics that are needed in data science.
be familiar with the use of linear programming in regressionunderstand the basics of ridge regression, the LASSO and smoothing splinesdevelop problem solving skills including via softwaredevelop communication skills
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Critically competent in a core academic discipline of their award
Students know and can critically evaluate and, where applicable, apply this knowledge to topics/issues within their majoring subject.
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Biculturally competent and confident
Students will be aware of and understand the nature of biculturalism in Aotearoa New Zealand, and its relevance to their area of study and/or their degree.
MATH203 or DATA203 or EMTH211
Students must attend one activity from each section.
Domestic fee $821.00
International fee $3,750.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see
Mathematics and Statistics