DATA203-26S1 (C) Semester One 2026

Data Science Multivariable Methods

15 points

Details:
Start Date: Monday, 16 February 2026
End Date: Sunday, 21 June 2026
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 1 March 2026
  • Without academic penalty (including no fee refund): Sunday, 10 May 2026

Description

This course develops foundations for data science techniques. The focus of this course is on applications to modern data processing problems. Students will be introduced to multivariate statistical, linear algebra and calculus topics that are needed in data science and related subjects.

Learning Outcomes

  • be familiar with standard techniques in linear algebra relevant to data science
  • be proficient with multivariate calculus techniques in probability
  • 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:

      Employable, innovative and enterprising

      Students will develop key skills and attributes sought by employers that can be used in a range of applications.

Prerequisites

One of DATA101, STAT101, MATH120 or EMTH119; and one of MATH102, MATH199 or EMTH118

Restrictions

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 11:00 - 12:00 Ernest Rutherford 465
16 Feb - 29 Mar
20 Apr - 31 May
Lecture B
Activity Day Time Location Weeks
01 Wednesday 13:00 - 14:00 Ernest Rutherford 465
16 Feb - 29 Mar
20 Apr - 31 May
Lecture C
Activity Day Time Location Weeks
01 Friday 10:00 - 11:00 Ernest Rutherford 465
16 Feb - 29 Mar
20 Apr - 31 May
Tutorial A
Activity Day Time Location Weeks
01 Friday 11:00 - 12:00 John Britten 117 HP Seminar Room
16 Feb - 29 Mar
20 Apr - 31 May
02 Friday 12:00 - 13:00 John Britten 117 HP Seminar Room
16 Feb - 29 Mar
20 Apr - 31 May
03 Thursday 12:00 - 13:00 James Logie 104
16 Feb - 29 Mar
20 Apr - 31 May

Course Coordinator

Christopher Price

Course links

Library portal
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Indicative Fees

Domestic fee $948.00

International fee $4,263.00

* 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 DATA203 Occurrences

  • DATA203-26S1 (C) Semester One 2026
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