COMP 2026 Visual Analytics
Credit Points 10
Legacy Code 301489
Coordinator Quang Vinh Nguyen Opens in new window
Description This subject introduces the fundamentals and technologies of visual analytics to understand big data. It covers major concepts of information visualisation, human computer perception and methods for visual data analysis. Students will learn knowledge and skills for identifying suitable visual analytics techniques, methods and tools for handling various data sets and applications. The subject provides students with opportunities to explore novel research in visual analytics and visualisation.
School Computer, Data & Math Sciences
Discipline Computer Science
Student Contribution Band HECS Band 2 10cp
Check your HECS Band contribution amount via the Fees page.
Level Undergraduate Level 2 subject
Restrictions
Students enrolled in programs other than the 3769 Bachelor of Data Science or 3770 Bachelor of Applied Data Science must have successfully completed 60 credit points.
Assessment
The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.
| Item | Length | Percent | Threshold | Individual/Group Task |
|---|---|---|---|---|
| Practical | 2 hours for each session | 20 | N | Individual |
| Report | 20-25 hours | 30 | N | Individual |
| Report | 20-25 hours | 30 | N | Group |
| Multiple Choice | 1 hour | 20 | N | Individual |
Teaching Periods
Autumn
Parramatta - Victoria Rd
Day
Subject Contact Quang Vinh Nguyen Opens in new window
View timetable Opens in new window
Sydney City Campus - Term 2
Sydney City
Day
Subject Contact Mahsa Razavi Opens in new window