Mathematics for Data Science 1 (MATH7501)
Information valid for Semester 1, 2017
Course level
Postgraduate Coursework
Faculty
School
Mathematics & Physics School
Units
2
Duration
One Semester
Delivery mode
Internal
Class hours
2 Lecture hours
1 Tutorial hour
1 Practical or Laboratory hour
Incompatible
MATH1050, MATH1061, MATH1051, MATH1052, MATH7861
Prerequisite
Qld Year 12 Maths B (or equivalent)
Assessment methods
Assignments and Examinations
Course enquiries
Current course offerings
Course offerings | Location | Mode | Course Profile |
Semester 1, 2025 (24/02/2025 - 21/06/2025) | St Lucia | In Person | Course Profile |
Please Note: Course profiles marked as not available may still be in development.
Course description
This course will provide students with the mathematical foundations needed for analytical and statistical data science. The course will introduce logic, proofs and the elementary properties of graphs which are used for modelling networks. Limits, sequences and series which form the basis of calculus are introduced. Derivatives, maxima/minima, integration and Taylor series. Extension to multi-dimensional problems. Partial derivatives, maxima and minima. Data fitting using least squares. Numerical integration and solution of non-linear equations. Linear Algebra. Vectors, linear independence, scalar product. Matrices, simultaneous equations, determinants, vector product, eigenvalues, eigenvectors, applications. Use of mathematical software for linear algebra applications.