Monash University Handbook 2011 Undergraduate - Area of Study

Twenty-first century science without computational support is practically unimaginable. Computational analysis and visualisation are the basis to cope with the vast amounts of data that modern science and engineering must process. Computers allow us to perform virtual experiments that are too dangerous, too costly, or plainly impossible to conduct in reality, and using simulation we can even explore hypothetical worlds. The computational science major complements computer science with foundational studies in another field of science and with specialised topics in scientific computation. It aims to produce graduates that combine a scientific education with computational expertise and are adept in trans-disciplinary work.

Minor in computational science

Students complete the following units:

• STA1010 Statistical methods for science or SCI1020 Introduction to statistical reasoning
• MTH2051 Introduction to computational mathematics or MTH3051 Introduction to computational mathematics
• FIT3143 Parallel computing
• FIT3139 Computational science

In addition students will replace:

(a.) MAT2003 Continuous mathematics for computer science with one of:

• MTH1030 Techniques for modelling
• ENG1091 Mathematics for engineering (with individual approval)

(b.) FIT2003 IT professional practice with one of:

• SCI2010 The practice and application of science
• SCI2020 Scientific methodologies and research techniques

It is also recommended that students complete one of the following as an elective:

• STA2032 Advanced data analysis
• STA2216 Data analysis for science

Major in computational science

Students complete the minor in computational science (above) plus either a minor in mathematics or a minor in a science area of study, such as biology, physics, chemistry, and biotechnology. Refer to the Science areas of study available for Clayton at http://www.monash.edu.au/pubs/2011handbooks/aos/index-ug-byfaculty-sci.html

Bachelor of Computer Science