STA5075Z - Statistical And High Performance Computing

12 credits at NQF level 9

Entry Requirements:

Acceptance into the Master’s course in Data Science or quantitative background deemed sufficient by Head of Department.

Course Outline:

This courses aims to provide students with a foundation in statistical computing for data science. The course is divided into three sections, namely Basic Programming, High Performance Computing and Simulation & Optimisation. In the first section, students will learn how to write computer programs to analyse data with the R Language and Environment for Statistical Computing. Students will then be taught how to run jobs in parallel on a remote computer cluster using a Linux command prompt. Finally, the course will introduce students to the fundamental principles and uses of simulation and optimisation.