Data Analytics

Key programme benefits to future students

How to apply human factors and ergonomic principles.



Tools to communicate business insights that will empower you to make strategic recommendations using R-Shiny data visualisations and digital dashboards.



A strengthened ability to analyse, summarise, visualise, and report on insights extracted from a dataset using real-world examples from your organisation.

Autumn Modules

• Introduction to Predictive Analytics

• Data Analytics with R (M)

• Future-Focused Professional Portfolio 1



Spring Modules

• Statistical Learning with Applications

• Advanced Predictive Analytics

• Future-Focused Professional Portfolio 2



Summer Modules

• Research Project

Students will specialise their dissertation studies in one of the three sub-disciplines: Mathematics and Statistics, Electronic and Computer Engineering, or Computer Science and Information Systems.

You are normally expected to hold a primary honours degree in a cognate discipline, (minimum H2.2), or equivalent and have at least 5 years of relevant industry/workplace experience.



Those who do not meet the minimum entry criteria may be considered in accordance with the University's policy on the Recognition of Prior Learning. Such applicants will be required to submit a portfolio to demonstrate their technical and/or management experience.



Alternative Entry Route applicants will be required to undertake an interview. This is to ensure they have the experience, motivation and ability to complete and benefit from this course.

1 year part-time, on-campus.

Spring

Graduate careers

“Learnings are immediately applicable from the business perspective & have an impact on our ability to deliver high value solutions to customers across the wide range of industries & markets we support.” Rosemary Ryan, Analog Devices