Advanced Discrete Mathematics (Classroom and Asynchronous)
About This Course
1. Define industry developments and trends in analytics, algorithms and statistical modelling and
carry out direct data analytics and statistical modelling efforts across the organisation. (K1, A1)
2. Define new and emerging data analytics and modelling tools and methodologies and make
decisions on appropriate data analytics and computational methodologies to the problem. (K2,
A2)
3. Define broad range of algorithms and advanced programming techniques, elements of complex
or advanced algorithms and computational models and design complex or advanced statistical
and computational models. (K3, K4, A3)
4. Define the applicability of various data analytics methodologies and techniques to address
different business issues and evaluate a broad range of algorithms and advanced
computational methods to determine suitability for business context. (K5, A4)
5. Lead the application of algorithms, models and computational techniques to new domains and
establish guidelines for the creation and selection of effective algorithms and statistical models.
(A5, A6)
6. Synthesise critical findings and insights to address a significant business need or problem. (A7)
What You'll Learn
mathematical toolbox of techniques needed of other units as well as to formulate a logical argument, construct a mathematical proof and understand and use simple probabilistic and statistical techniques.
Entry Requirements
1. Minimum a Diploma from a recognised institute
2. Admission consideration may be given on a case by case basis to learners who may not meet
the above entry requirements but has extensive and relevant working experiences
3. At least a C6 pass for English (EL1) at GCE ‘O’ Levels or equivalent
4. Recommended to have basic computer operating knowledge