University of Technology Sydney

94689 Special Subject 1 (FTDI)



This subject is intended for students in the Master of Data Science and Innovation (C04372) who are in their final stage of the course and have 2 credit points remaining in order to fulfil the requirements for the degree. The study load of this subject is about 3-4 hours per week, or about 35 hours in total, for one assignment. It can be taken as a self-study course or as a small project. In either case, the topic should be related to data science. Example of a project: sentiment analysis of political autobiographies. Example of self-study: data wrangling with pandas, or an online short course. An academic advisor needs to be organised by the student. Any UTS faculty including the subject coordinator, or a suitably qualified external professional can be the advisor.

The procedure for enrolment is: students write a one-page proposal inclduing the assessment task, for which the academic advisor has agreed to supervise and assess the work. Next, send the proposal to the subject coordinator for approval. Then students submit an e-request together with the subject coordinator’s approval to Student Centre for enrolment.

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.