MA5801 - Essential Mathematics for Data Scientists
|Student Contribution Band:
||College of Science and Engineering
Data Science is grounded in mathematics. This subject will provide students with the
essential elements of mathematics required for data scientists. This subject will
include elements of discrete mathematics including logics, sets, proof, functions,
relations, graphs and trees. It will also include elements of linear algebra including
linear systems and matrix formulation, vector spaces, eigenvalues/eigenvectors, singular
value decomposition as well as optimization and numerical methods. Computational aspects
of this course will be developed in MatLab.
- identify and apply concepts of set theory, arithmetic, logic, proof techniques, binary
relations, graphs and trees to solve problems in data science;
- apply linear algebra and numerical mathematics concepts for optimisation and dimensionality
reduction in data science problems;
- apply and implement concepts in discrete mathematics, optimisation and linear algebra
in data science using MatLab.
- Invigilated > Quizzes or tests - (20%)
- Non-Invigilated > Assignments - (60%)
- Computational laboratories/log book - (20%).
Study Period 84
|Census Date 16-Jul-2020
||Assoc. Professor Shaun Belward.
The student workload for this
credit point subject is approximately
- 65 hours
- assessment and self-directed study
|Method of Delivery:
||Online - JCU
Minor variations might occur due to the continuous Subject quality improvement process,
and in case
of minor variation(s) in assessment details, the Subject Outline represents the latest