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 2024 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 to complete the course with 96 credit points. 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 an online self-study course or as a small project. In either case, the topic should be related to data science. Example of project: sentiment analysis of political autobiographies. Example of online self-study: data wrangling with pandas.

For the small project, an academic advisor needs to be organised by the student. Any UTS faculty, or a suitably qualified external professional can be the advisor. At the beginning of the semester, students write a one-page proposal including the assessment task, for which the academic advisor has agreed to supervise and assess the work. For the online self-study course, it should include assessment tasks with a certificate of completion.