DATA420-26S2 (C) Semester Two 2026

Scalable Data Science

15 points

Details:
Start Date: Monday, 13 July 2026
End Date: Sunday, 8 November 2026
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 26 July 2026
  • Without academic penalty (including no fee refund): Sunday, 27 September 2026

Description

This course will introduce students to core topics in scalable data science based on distributed-computing techniques. This is a very practical course, with students learning by experimenting on a computer cluster.

Prerequisites

Subject to approval of the Head of Department of Mathematics and Statistics.

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Monday 14:00 - 15:00 F3 Lecture Theatre
13 Jul - 23 Aug
7 Sep - 18 Oct
Lecture B
Activity Day Time Location Weeks
01 Tuesday 14:00 - 16:00 E16 Lecture Theatre
13 Jul - 23 Aug
7 Sep - 18 Oct
Computer Lab A
Activity Day Time Location Weeks
01 Thursday 12:00 - 13:00 Jack Erskine 035 Lab 2
13 Jul - 23 Aug
7 Sep - 18 Oct
02 Wednesday 12:00 - 13:00 Jack Erskine 035 Lab 2
13 Jul - 23 Aug
7 Sep - 18 Oct
03 Wednesday 16:00 - 17:00 Jack Erskine 035 Lab 2
13 Jul - 23 Aug
7 Sep - 18 Oct
04 Wednesday 17:00 - 18:00 Jack Erskine 035 Lab 2
13 Jul - 23 Aug
7 Sep - 18 Oct

Additional Course Outline Information

Assessment and grading system

• Labs / exercises 10%
• Quizzes 10%
• Assignment 1 40%
• Assignment 2 40%

Indicative Fees

Domestic fee $1,247.00

* 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 .

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