DATA425-26S1 (C) Semester One 2026

Foundations of Deep Learning

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

The aim of this course is to introduce students to foundational concepts of deep neural networks. The focus of this course is on both fundamental and applied methods in deep neural networks. A range of topics from convolutional and recurrent type networks to neural-network generative models and attention mechanisms will be introduced.

Prerequisites

Subject to HoS approval

Restrictions

Timetable 2026

Students must attend one activity from each section.

Lecture A
Activity Day Time Location Weeks
01 Tuesday 16:00 - 17:00 Ernest Rutherford 225
16 Feb - 29 Mar
20 Apr - 31 May
Lecture B
Activity Day Time Location Weeks
01 Friday 12:00 - 13:00 Ernest Rutherford 225
16 Feb - 29 Mar
20 Apr - 31 May
Computer Lab A
Activity Day Time Location Weeks
01 Thursday 10:00 - 11:00 Jack Erskine 442 Computer Lab
16 Feb - 29 Mar
20 Apr - 31 May

Assessment

Assessment Due Date Percentage  Description
Theoretical foundations 20% Theoretical foundations
Reproducibility study 20% Reproducibility study
Review of research paper 20% Review of research paper
Exam 40% Exam

Course links

Library portal

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 .

All DATA425 Occurrences

  • DATA425-26S1 (C) Semester One 2026