Courses - Faculty of Science
Data Science
Stage I
Data Science for Everyone
Explores how to use data to make decisions through the use of visualisation, programming/coding, data manipulation, and modelling approaches. Students will develop conceptual understanding of data science through active participation in problems using modern data, hands-on activities, group work and projects. DATASCI 100 will help students to build strong foundations in the science of learning from data and to develop confidence with integrating statistical and computational thinking.
Stage III
Capstone: Creating Value from Data
A group-based project in which students showcase their skills in collaboratively creating value from data. Within a given data science domain, teams will jointly develop a research question, apply their skills to gather, structure, and analyse data to address the question, and communicate their findings effectively. The insights, their implications, limitations, and future work will be discussed by the group. Each team member will write an individual report about the project.
Prerequisite: 30 points at Stage III in Data Science
Postgraduate 700 Level Courses
Data Management
Data management is the practice of collecting, preparing, organising, storing, and processing data so it can be analysed for business decisions. The course will use R and SQL to illustrate the process of data management. This will include principles and best practice in data wrangling, visualisation, modelling, querying, and updating.
Prerequisite: COMPSCI 130, MATHS 108, and 15 points from STATS 101, 108, or equivalent
Restriction: COMPSCI 351, 751, STATS 383, 707, 765
Statistical Computing Skills for Professional Data Scientists - Level 9
Fundamental topics taught in statistical computing and data management including use of data analytic software such as Excel and R for data analysis, programming, graphics, cleaning and manipulating data, use of regular expressions, mark-up languages LaTeX, and R Markdown, use of SQL and DBMSs, reproducible research and symbolic computation. Students will undertake assigned individual research projects to be presented in-class.
Prerequisite: 15 points from ENGSCI 314, STATS 201, 208, 707
Restriction: STATS 779
Research Project - Level 9
To complete this course students must enrol in DATASCI 791 A and B, or DATASCI 791