Faculty notice: this unit is changing
Move to S1 Final offering S1 2027
BCS - Data science (2024)
Replace with FIT2179 from 2028 (S1)
From: Re-enrolment and unit changes - Information Technology (undergraduate) · Last checked: 7 Oct 2026 UTC
Official wording from the faculty, shown as published. It is the page of the Faculty of IT on monash.edu, so confirm with your faculty that it applies to your campus and intake year. Replacements are decided by the faculty, not by this site.
Units / FIT3179
FIT3179 · Data visualisation
2027 Handbook6 credit pointsLevel 3Faculty of Information Technology
Overview
Data visualisation is a powerful technique that allows us to use our visual system to understand data. Interactive data visualisation is now common in business, engineering and design and the social and physical sciences. This unit introduces the main kinds of information graphics and interactive visualisation systems and their areas of application. It investigates the reasons why visualisation can be effective and based on this you will gain experience in critically assessing data visualisations and in designing your own visualisations. You will learn how to create visualisations with representative computer tools and gain experience in creating a data visualisation for an application domain of their choice.
Areas of study: Business analytics Computational science Data science Digital humanities
Offerings
| Campus | Teaching period | Mode |
|---|---|---|
| Clayton | First semester | Teaching activities are on-campus (ON-CAMPUS) |
Assessment
The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.
| # | Assessment | Type | Weight | Hurdle |
|---|---|---|---|---|
| 1 | Studio Tasks | Exercise | 15% | — |
| 2 | Class Tests | Quiz / Test | 35% | — |
| 3 | Data Visualisation I | Project | 25% | — |
| 4 | Data Visualisation II | Project | 25% | — |
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Requisites
prohibition
prerequisite
OR
FIT1053Introduction to programming (Advanced)6 cpOR
FIT1008Fundamentals of algorithms6 cpOR
FIT1054Fundamentals of algorithms (Advanced)6 cpOR
FIT2085Fundamentals of algorithms for engineers6 cpOR
ENG1013Engineering smart systems6 cpOR
ENG1014Engineering numerical analysis6 cpOR
FIT1048Fundamentals of C++6 cpOR
FIT1051Programming fundamentals in java6 cpLearning outcomes
- Critically analyse data visualisations;
- Create effective data visualisations;
- Describe the main applications of data visualisation in business, engineering and design, and the social and physical sciences;
- Describe the advantages, drawbacks and pitfalls of the visual presentation of data as compared to its presentation using other media.
Workload
Minimum total expected workload to achieve the learning outcomes for this unit is 144 hours per semester typically comprising a mixture of scheduled online and face to face learning activities and independent study. Independent study may include associated reading and preparation for scheduled teaching activities.
| Activity | Duration |
|---|---|
| Studio activities | 24 hours |
| Workshops | 24 hours |
Ask about FIT3179
Answered from the Handbook fields above — no AI, no guessing. Every answer links back to the source.
Community discussions about FIT3179
CommunityStudent experience, not official rules. Nothing here changes what the Handbook says.