Course Details

Who is the course for?

The course is particularly suitable for those with numeracy skills who wish to work as data analysts, business analysts or to enter into management roles across a range of sectors. You do not need to have previously studied programming. However, given the timeframe and the amount of technical and statistical content, applicants should be prepared to commit fully to the course.

Entry Requirements

Applicants holding an honours degree (level 8 or equivalent) in any discipline will be considered. Candidates will ideally be able to demonstrate technical or mathematical problem-solving skills as part of previous course learning. Typically holders of more technical, numerate degrees are likely to gain a higher ranking in any order of merit in selection for the course.

For candidates who do not have a level 8 qualification the college operates a Recognition of Prior Experiential Learning (RPEL) scheme meaning applicants who do not meet the normal academic entry requirements may be considered based on relevant work or other experience.

This programme has a BYOD (Bring Your Own Device) policy. Specifically, students are expected to successfully participate in lectures, laboratories and projects using a portable computer (laptop/notebook) with a substantial hardware configuration. Its minimal suitable configuration is 8GB of RAM (16GB are recommended); a modern 64-bit x86 multi-core processor (Intel i5 or superior); 250+ GB of available space in hard disk; WiFi card; and a recent version of Ubuntu, macOS, or Windows

Duration

This course runs over 1 year; 3 semesters

Course Fee

This course costs €4,500 (Fees revised annually)

Award and Progression

Higher Diploma in Science in Data Analytics is awarded by QQI at level 8 on the National Framework of Qualifications. Students who successfully complete this course may be eligible to progress to a major award at level 9 on the NFQ.

According to a recent Higher Education Outcomes Report released by the CSO, ICT graduates receive the highest weekly earnings five years after graduating compared to other sectors based on the analysis of the destinations of students who graduated between 2010 and 2016.

Assessment

The course will be assessed with a blend of continuous assessments and/or project works and exams. This varies between modules but typically assessment is split 60:40 between exams and continuous assessment. Please note that in some instances exams may take place in the daytime and at weekends.