PDip Data Analytics and Visualisation

This course is designed to reskill and upskill graduates to prepare them to take up the increasing opportunities to work as data analysts, who are in demand across multiple sectors, including Financial, Government, Manufacturing, Food, Health and Media.
The course emphasises the development of strong theoretical and applied foundations, and builds on our existing strengths in Data Science and Analytics in the School of Computer Science and the Insight Institute, and our experience in running a successful Masters in Data Analytics.

The programme has a number of core elements:
Immersion in fundamental database and software development techniques. A solid foundation in statistical and analysis methods.
Expertise in data analysis, visualisation and business intelligence using leading edge tools and programming languages.
Capstone project to deepen and demonstrate students acquired skills.
A significant placement/internship allowing participants to gain relevant experience and also provide Industry Partners with an opportunity to assess potential recruits.
Career Opportunities
The Postgraduate Diploma in Data Analytics responds to a strong and growing demand for graduates with skills in data analysis across all industry sectors. Every industry has seen a huge growth in the amount of data which they generate and collect, which represents a very valuable resource for companies. Demand for workers with specialist data skills like data scientists and data engineers has increased dramatically over the past five years according to recent surveys. Roles that will be suitable for graduates of this programme include: Data Analysts, Data Visualisation Specialists, Data Engineers, Data Scientists, Business Analytics Specialist
Business Intelligence Developer

Applicants are normally required to hold a minimum of a Level 8 honours qualification (2.2 or higher) or equivalent in a cognate discipline. Graduates with a Level 7 degree and relevant practical industry experience in the area of computing and information technology will also be considered. Graduates from non-STEM (Science, Technology, Engineering, and Mathematics) disciplines such as languages will be welcomed, but will need to demonstrate an aptitude for logical thinking and problem solving. The application process will include interviews and/or aptitude tests, given that the placement is a key element of the programme.

The programme is in line with the University Policy for Recognition of Prior Learning in that it recognises prior academic qualifications. The aim of this initiative is to provide graduates with the opportunity to acquire qualifications for employment in the data analytics field. RPL applications are also welcome and can be completed by contacting the Programme Director.

Recognition of Prior Learning (RPL)

The programme is in line with the University Policy for Recognition of Prior Learning in that it recognises prior academic qualifications. The aim of this initiative is to provide graduates with the opportunity to acquire qualifications for employment in the data analytics field. RPL applications are also welcome and can be completed by contacting the Programme Director.

English Language Requirements

IELTS: 6.5 overall, no less than 5.5 in any one component; Cambridge C1 Advanced (CAE): 176 overall; Cambridge C2 Advanced (CPE): 180 overall; TOEFL: 88 overall (7 Listening, 16 Speaking, 18 Writing, 8 Reading); Pearson PTE: 61 overall, no less than 48 in any one component.