MA5801 - Essential Mathematics for Data Scientists

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.

Learning Outcomes

• 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.

Subject Assessment

• Written > Examination - In class - (20%) - Individual
• Written > Test/Quiz 1 - (10%) - Individual
• Written > Problem task - (50%) - Individual
• Written > Workbook - (20%) - Individual.

Note: 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 official information.