94689 Special Subject 1 (FTDI)

Warning: The information on this page is indicative. The subject outline for a particular session, location and mode of offering is the authoritative source of all information about the subject for that offering. Required texts, recommended texts and references in particular are likely to change. Students will be provided with a subject outline once they enrol in the subject.

Subject handbook information prior to 2023 is available in the Archives.

Description

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.