DATA473-23S2 (C) Semester Two 2023

Special Topic

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


Special Topic

Algorithms in Data Science

Scalability, the subject of study in this course, has recently become one of the central topics in Data Science (DS), Machine Learning (ML), and Artificial Intelligence (AI). For example, artificial neural network based natural language models have shown their true potential only when their size has reached billions, or even hundreds of billions, of parameters; to achieve human level accuracy at the protein structure prediction problem a deep learning algorithm requires dozens of powerful (A100) GPUs to be trained on.

In this course we will study what it means for an algorithm to scale and how to design and implement scalable algorithms. Starting from basic methods of algorithm design and analysis, we will consider what breakthroughs in algorithms made modern AI, ML, and DS possible, and what algorithmic challenges remain to be solved to enable future generations of scalable data-intensive computational methods.

Learning outcomes of this course include basic skills in algorithm design and analysis in the context of modern deep learning (DL). For example, students will be able to design, implement, and analyze a transformer-based DL model. All algorithms will be illustrated with their applications in biological data science, which will equip the learner with transferable skills.


Subject to the approval of the Head of School.

Course Coordinator

Alex Gavryushkin

Indicative Fees

Domestic fee $995.00

International fee $4,250.00

* 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 DATA473 Occurrences

  • DATA473-23S2 (C) Semester Two 2023