University of Technology Sydney

37373 Programming for Data Analysis

6cp; Forms of attendance in this subject have changed to enable social distancing and reduce the risks of spreading COVID-19 in our community. There may also have been changes to the assessment requirements. Consequently, the Subject Outline information for this subject has changed. Details of the changes may be published in an Addendum to the Subject Outline which is available through your LMS (Blackboard or Canvas).
Requisite(s): 37171 Introduction to Programming for Mathematics AND (((35212 Computational Linear Algebra OR 37233 Linear Algebra)))
These requisites may not apply to students in certain courses. See access conditions.
Anti-requisite(s): 35383 Programming for Mathematical Modelling and Data Analysis


The goal of this subject is to introduce students to data structures and programming techniques that can be used to collect, manipulate, model, and analyse a broad range of datasets, including datasets with missing values. It uses the Python programming language to learn how to work with numerical, string, and more complex data formats, and to perform basic mathematical modelling or statistical analyses based on the data. The subject places a strong emphasis on developing a clear understanding of the common features of data structures from diverse areas, which may include nonlinear dynamics, discrete optimisation, mathematical physics, statistics, computational biology, or stochastic processes. Students develop practical skills in problem solving by working on a real-world data analysis project of their choosing, using publicly available datasets.

Typical availability

Autumn session, City campus

Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.