This computing course aims to produce high-quality, technically competent, innovative graduates that will become leading practitioners in the field of data analytics.
Upon completion of this course, graduates will be able to:
The course structure accommodates a
wide audience of learners whose specific
interests in data analytics may be either
technically focused or business focused.
All students will also gain exposure
to pertinent legal issues and product
associated with the data analytics field.
The course will be delivered using academic
research, industry-defined practical
problems, and case studies. This approach
will naturally foster a deeper knowledge
of the subject area and create transferable
skills for work such as critical thinking,
problem-solving, creative thinking,
communication, teamwork and research
skills. The course is completely delivered
by faculty and industry practitioners with
proven expertise in data analytics.
For information on the modules taught on this course view our module descriptors.
The Master of Science in Data Analytics is
awarded by QQI at level 9 on the National
Framework of Qualifications. Students who
successfully complete this course may
progress to a major award at level 10 on the
NFQ. Students may also elect to exit early
with the Postgraduate Diploma in Science
in Data Analytics at level 9 on the NFQ.
This course runs over 2 years; 4 semesters.
€4,475 per annum, €8,950 total fee.
(Fees revised annually)
You can spread the cost of this course with a direct debit plan.
This course is ideal for graduates that are
looking to progress into the emerging
data analytics market to increase their
employment potential. The course is
suitable for graduates who have technical
or mathematical problem-solving skills.
Graduates from disciplines that have not
developed these skills will need to be able
to demonstrate an aptitude for technical or
This course takes place two evenings per week from 6pm-10pm and every second Saturday. This schedule is for indicative purposes only. Days and times are subject to change.
Please note that exams can be scheduled during the morning, afternoon or evening Monday to Saturday.
An indication of the content covered on the course is:
To find out more about the subjects taught on this course view the module descriptor.
Students on the course also have free access to DataCamp. Datacamp allows students to revisit and reinforce the knowledge acquired during lectures when and where they like.
A minimum of a level 8 (honours degree) qualification(2.2 or higher) on the National Qualifications Framework. Applicants may be from a cognate/STEM background and standard applicants for the programme are those holders of computing or numerate degrees.
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. Non-English speaking applicants must demonstrate fluency in the English language as demonstrated by an IELTS academic score of at least 6.5 or equivalent.
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. The 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.
It is the responsibility of each student to ensure their computer is functioning correctly and that they have full administrator rights. NCI IT cannot provide support for these personal devices.