FIT3139 Computational modelling and simulation
Faculty of Information Technology
FIT3139 Computational modelling and simulation is a level 3, 6-credit-point, undergraduate unit from the Faculty of Information Technology, offered in 2027 in Semester 1 at Clayton. It needs (FIT1058, MAT1841, ENG1005, MTH1030 or MTH1035) and (FIT1008, FIT1054 or FIT2085).
- Credit points
- 6
- Offered in 2027
- Semester 1
- Clayton
- Assessment
- No exam
- 4 tasks
- Workload
- 144 hours
- per semester
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Requisites
Before FIT3139
Prerequisites
Pass these before you enrol.
After FIT3139
No unit lists FIT3139 as a prerequisite in the 2027 handbook.
Overview
This unit provides an overview of computational science and an introduction to its central methods. It covers the role of computational tools and methods in 21st century science, emphasising modelling and simulation. It introduces a variety of models, providing contrasting studies on: continuous versus discrete models; analytical versus numerical models; deterministic versus stochastic models; and static versus dynamic models. Other topics include: Monte-Carlo methods; epistemology of simulations; visualisation; high-dimensional data analysis; optimisation; limitations of numerical methods; high-performance computing and data-intensive research.
A general overview is provided for each main topic, followed by a detailed technical exploration of one or a few methods selected from the area. These are applied workshops which also acquaint you with standard scientific computing software (e.g., Mathematica, Matlab, Maple, Sage). Applications are drawn from disciplines including Physics, Biology, Bioinformatics, Chemistry, Social Science.
Offerings in 2027
| Teaching period | Campus | Mode |
|---|---|---|
| First semester | Clayton | Flexible |
Assessment
- Assignment Part 1Exercise15%
- Assignment Part 2Project25%
- Final ProjectProject50%
- QizzesQuiz / Test10%
Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.
Learning outcomes
When you finish this unit, you should be able to:
- 1
Explain and apply the process of computational scientific model building, verification and interpretation;
- 2
Analyse the differences between core classes of modelling approaches (Numerical versus Analytical; Linear versus Non-linear; Continuous versus Discrete; Deterministic versus Stochastic);
- 3
Evaluate the implications of choosing different modelling approaches;
- 4
Rationalise the role of simulation and data visualisation in science;
- 5
Apply all of the above to solving idealisations of real-world problems across various scientific disciplines.
Workload and teaching
- Applied sessions24 hours
- Workshops24 hours
- Teaching approachCase-based teaching
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.
The teaching and learning approach provides facilitated learning and practical exploration of case studies to develop real-world skills.
Where it fits
FIT3139 is part of 1 area of study in the 2027 handbook.
Contacts
- Chief Examiners
- Associate Professor Julian Garcia Gallego
Common questions
What are the prerequisites for FIT3139?
You need (FIT1058, MAT1841, ENG1005, MTH1030 or MTH1035) and (FIT1008, FIT1054 or FIT2085) before you enrol.
When is FIT3139 offered?
In 2027, FIT3139 runs in Semester 1 at Clayton.
How much work is FIT3139?
The handbook expects about 144 hours of study across the semester. No students have rated its difficulty yet.
Does FIT3139 have an exam?
No. FIT3139 has 4 assessment tasks and no exam.
Which majors and minors include FIT3139?
FIT3139 is part of Software engineering.