Mathematics for Data Science 1 (MATH7501)
Information valid for Semester 1, 2023
Course level
Postgraduate Coursework
Faculty
School
Mathematics & Physics School
Units
2
Duration
One Semester
Attendance mode
External
Class hours
Lecture 2 Hours/ Week
Tutorial 1 Hour/ Week
Practical 1 Hour/ Week
2L1T1P
Incompatible
MATH1050, MATH1061, MATH1051, MATH1052, MATH7051, MATH7052, MATH7861
Prerequisite
A grade of C or higher in Queensland Year 12 Mathematical Methods (Units 3 & 4) (or equivalent).
Assessment methods
Assignments, 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.
