DATA416-23S1 (D) Semester One 2023 (Distance)

Contemporary Issues in Data Science

15 points

Details:
Start Date: Monday, 20 February 2023
End Date: Sunday, 25 June 2023
Withdrawal Dates
Last Day to withdraw from this course:
  • Without financial penalty (full fee refund): Sunday, 5 March 2023
  • Without academic penalty (including no fee refund): Sunday, 14 May 2023

Description

This course focuses on the technical challenges in data science that societal and regulatory actions pose. It aims to introduce students the often very different and sometimes even conflicting perspectives from which policymakers and the technical community approaches these problems. We will review and discuss different examples from different areas of data science such as the extent to which machine learning and deep learning techniques conform with GDPR regulations on transparency, explainability, and accountability; impossibility theorems showing off the limits of data science methods; the mathematical foundations and data science techniques for mechanism design in order to manipulate beliefs (represented as transitive, anti-symmetric, and complete binary relations); and provide students as potential future product developers with the necessary knowledge to engage in responsible product development practices that are informed by regulatory requirements and expectations. This course develops students' understanding of the role of data science in decision making and the impact of data science in the design of AI systems. The course reflects the main issues of controversy identified in international policy debates.

Prerequisites

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

Course Coordinator

Gabor Erdelyi

Indicative Fees

Domestic fee $995.00

* 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 DATA416 Occurrences

  • DATA416-23S1 (C) Semester One 2023
  • DATA416-23S1 (D) Semester One 2023 (Distance)