Course Details

About this Course

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 commercialisation considerations 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.

Who is the course for?

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 mathematical problem solving.

Course Content

For information on the modules taught on this course view our module descriptors.

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.

Award and Progression

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.

Entry Requirements

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.

Indicative Schedule

Students need to be available 09.00-18.00 Mon – Fri (class days and times vary).

Please note that exams can be scheduled during the morning, afternoon or evening Monday to Saturday.

Duration

This course runs over 1 year; 2 semesters with a final research project.

Course Fee

€6,500 total fee (Fees revised annually)

You can spread the cost of this course with a direct debit plan.

International Students' Fees

The fee for this course for international students is €14,500.

Find out more about studying here as an international student.