DATA303-24S2 (C) Semester Two 2024

Computational Data Methods

15 points

Details:
Start Date: Monday, 15 July 2024
End Date: Sunday, 10 November 2024
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 28 July 2024
  • Without academic penalty (including no fee refund): Sunday, 29 September 2024

Description

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 total least squares
  • 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.

Prerequisites

Restrictions

Timetable 2024

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 11:00 - 12:00 A7
15 Jul - 25 Aug
9 Sep - 20 Oct
Lecture B
Activity Day Time Location Weeks
01 Wednesday 09:00 - 10:00 A7
15 Jul - 25 Aug
9 Sep - 20 Oct
Tutorial A
Activity Day Time Location Weeks
01 Monday 14:00 - 15:00 Jack Erskine 235
15 Jul - 25 Aug
9 Sep - 20 Oct
02 Monday 09:00 - 10:00 Jane Soons 608
15 Jul - 25 Aug
9 Sep - 20 Oct

Course Coordinator

Christopher Price

Assessment

Assessment Due Date Percentage  Description
Tutorials 10% Tutorials start in week 2 of the semester, and run weekly thereafter. Tutorial questions will be posted on learn before the tutorial, followed by the answers afterwards. Each tutorial is worth one percent, up to a maximum of 10 percent. There are 11 tutorials in to
Assignments 20% There will be two assignments, each worth 10%. There will be one assignment in each term, with a minimum of two weeks to do the assignment.
Test 25% The test is worth 25%. It is open book online and will be held on a weekday (not Friday) evening of either the second or third week of term 4.
Final Examination 45% The final examination will be two and a half hours long and held in the end-of-year examination period. A minimum of 35% in the final exam is needed to pass the course. The School reserves the right to revise this minimum downwards

Indicative Fees

Domestic fee $844.00

International fee $3,950.00

* 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

  • DATA303-24S2 (C) Semester Two 2024
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