DATA303-23S2 (C) Semester Two 2023

Computational Data Methods

15 points

Start Date: Monday, 17 July 2023
End Date: Sunday, 12 November 2023
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 30 July 2023
  • Without academic penalty (including no fee refund): Sunday, 1 October 2023


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.

Learning Outcomes

  • be familiar with the use of linear programming in regression
  • understand the basics of ridge regression, the LASSO and smoothing splines
  • develop problem solving skills including via software
  • develop communication skills
    • University Graduate Attributes

      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.



Course Coordinator

Christopher Price

Indicative Fees

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 .

All DATA303 Occurrences

  • DATA303-23S2 (C) Semester Two 2023