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Unit of study_
COSC2902: Computational Modelling (Advanced)
2024 unit information
This unit will introduce a wide range of modelling and simulation techniques for tackling real-world problems using a computer. Data is often expensive to obtain, so by harnessing the enormous computational processing power now available to us we can answer what if questions based on data we already have. You will learn how to break a problem down into its key components, identifying necessary assumptions for the purposes of simulation. You will learn how to develop suitable metrics within computational models, to allow comparison of simulation data with real-world data. You will learn how to iteratively improve simulations as you validate them against real results, and you will gain experience in identifying the types of exploratory questions that computational modelling opens up. Programming will be in python. You will learn how to generate probabilistic data, solve systems of differential equations numerically, and tackle complex adaptive systems using agent-based models. Dynamical systems ranging from traffic flow to social segregation will be considered. By doing this unit you will develop the skills to go behind your data, understand why the data you observe might be as it is, and test scenarios which might otherwise be inaccessible. This is an advanced unit. It runs jointly with the associated mainstream unit, however the lab work and assessment requires a greater level of academic rigour. You will be required to engage in more challenging real-world computational modelling problems than the mainstream unit, and explore more deeply the reasons behind simulation results.
Unit details and rules
Managing faculty or University school:
Physics Academic Operations
| Code | COSC2902 |
|---|---|
| Academic unit | Physics Academic Operations |
| Credit points | 6 |
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Prerequisites:
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48 credit points of 1000 level units with an average of 65 |
|---|---|
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Corequisites:
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None |
| Prohibitions:
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COSC1003 or COSC1903 or COSC2002 |
| Assumed knowledge:
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HSC Mathematics; DATA1002, or equivalent programming experience, ideally in Python |
At the completion of this unit, you should be able to:
- LO1. given a real-world problem, develop a simplified model
- LO2. identify and explain assumptions underpinning a model of a real-world problem
- LO3. obtain a solution to a model using a computer
- LO4. given a computational model, and simulation output, identify key characteristics of the numerical solution
- LO5. check validity of simulation output and be able to defend conclusions
- LO6. develop and use metrics to compare simulation and real-world data.
Unit availability
This section lists the session, attendance modes and locations the unit is available in. There is a unit outline for each of the unit availabilities, which gives you information about the unit including assessment details and a schedule of weekly activities.
The outline is published 2 weeks before the first day of teaching. You can look at previous outlines for a guide to the details of a unit.
Modes of attendance (MoA)
This refers to the Mode of attendance (MoA) for the unit as it appears when you’re selecting your units in Sydney Student. Find more information about modes of attendance on our website.
Important enrolment information
Departmental permission requirements
If you see the ‘Departmental Permission’ tag below a session, it means you need faculty or school approval to enrol. This may be because it’s an advanced unit, clinical placement, offshore unit, internship or there are limited places available.
You will be prompted to apply for departmental permission when you select this unit in Sydney Student.
Read our information on departmental permission.
