MAT1841 - Mathematics for computer science 1
6 points, SCA Band 0 (NATIONAL PRIORITY), 0.125 EFTSL
Undergraduate Faculty of Information Technology
Leader(s): Clayton - Tom Hall; Malaysia - Tham Weng Kee
Linear algebra: vectors and matrices, Matrix algebra with applications to flow problems and Markov chains; matrix inversion methods. Probability and combinatorics: elementary probability theory, random variables, probability distributions, expected value; counting arguments in combinatorics; statistics for Experimental Design. Calculus: Partial differentiation, finding maximum and minimum of functions of several variables and constructing Taylor series expansions.
On completion of this unit students will have a working knowledge and an understanding of basic linear algebra, elementary probability theory, the basic principles of experimental design, counting principles in combinatorics and basic calculus that are used in computer science. Students will have gained the skills to manipulate matrices, design simple quantitative experiments, differentiate functions and find local maxima and local minima of functions of several variables, and construct Taylor series for functions.
Examination (3 hours): 70%
Three x 1hr lectures/week, one x 1hr support/week
VCE Mathematical Methods units 3 and 4