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.
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.
Rationalise the role of simulation and data visualisation in science;
Explain and apply the process of computational scientific model building, verification and interpretation;
Evaluate the implications of choosing different modelling approaches;
Analyse the differences between core classes of modelling approaches (Numerical versus Analytical; Linear versus Non-linear; Continuous versus Discrete; Deterministic versus Stochastic);
Apply all of the above to solving idealisations of real-world problems across various scientific disciplines.
Company
About UsMetaverse ClassroomNews & BlogJR CareersBecome a MentorOur MentorsContact UsJR Store J3.ClubResources
Job ReferralsEvents1-on-1 TutoringIndustry WhitepapersOnline LearningInterview CenterShare Interview ExperienceInternshipMembershipImmigration Services
Australia ImmigrationSkilled Visa 189/190/491Employer Sponsored 482/186/494Business Visa 188/888UK ImmigrationUS ImmigrationCanada ImmigrationEnterprise
P3 Career IncubatorEnterprise (EN)Corporate TrainingInternship PartnershipRecruitment PartnershipApply for PartnershipTop Categories
Web Full-Stack BootcampDevOps BootcampData Engineering BootcampData Analysis BootcampCoding for BeginnersBusiness Analyst InternshipAlgorithm BootcampCareer Services
BA & PM InternshipData Science InternshipData Analysis InternshipMarketing InternshipResume ReviewInterview CoachingVIP Mentor GuidanceAddresses
Level 10b, 144 Edward Street, Brisbane CBD(Headquarter)Level 2, 171 La Trobe St, Melbourne VIC 3000四川省成都市武侯区桂溪街道天府大道中段500号D5东方希望天祥广场B座45A13号Business Hub, 155 Waymouth St, Adelaide SA 5000Disclaimer
JR Academy acknowledges Traditional Owners of Country throughout Australia and recognises the continuing connection to lands, waters and communities. We pay our respect to Aboriginal and Torres Strait Islander cultures; and to Elders past and present. Aboriginal and Torres Strait Islander peoples should be aware that this website may contain images or names of people who have since passed away.
All content on the JR Academy website, including course materials, logos, and information provided, is protected under Australian intellectual property laws. Unauthorized use, sale, distribution, reproduction, or modification is strictly prohibited. Violations may result in legal action. By accessing our website, you agree to respect our intellectual property. JR Academy Pty Ltd reserves all rights, including patents, trademarks, and copyrights. Any infringement will be subject to legal prosecution. View Terms of Service
© 2017-2026 JR Academy Pty Ltd. All rights reserved.
ABN 26621887572
