STA5073Z - Data Science For Industry

15 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:

The goal of the module is to provide an applied, hands-on overview of selected topics useful in the working world of data science that are not covered by other modules in the program. Topics fall into two themes: workflow/productivity tools and skills; and modelling. Under the workflow theme we cover data wrangling (reading/writing data, webscraping, accessing APIs), version control with Git, and visualization and communication of data and results (ggplot2, R shiny). Under the modelling theme we cover recommender systems, text mining and basic natural language processing, and feedforward and convolutional neural networks.