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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:

• Conduct independent research and analysis in the field of data analytics

• Implement a research idea using the latest industry practices

• Demonstrate expert knowledge of data analysis and statistics

• Critically assess and evaluate business and technical strategies for data analytics

• Develop and implement business and technical solutions for data analytics

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.

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

minimum of a level 8 (honours degree) qualification (2.2 or higher) on the National Qualifications Framework. Applicants may be from a cognate/STEM or non– cognate background. Candidates from a non-cognate background may be called for interview. 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 IELTS academic score of at least 6.5 or equivalent.

This programme has BYOD (bring your own device) policy. Specifically, students are expected to successfully participate in lecturers, laboratories and projects using a laptop computer with a substantial hardware configuration.

Duration

Part-time Schedule
Indicative Schedule
Two evenings per week, 18.00 - 22.00 and every second Saturday.

Duration 2 years; 4 semesters

https://www.ncirl.ie/Courses/Course-Details/course/MSc-in-Data-Analytics...

Full-time Schedule
Indicative Schedule Students need to be available 09.00-18.00 Mon – Fri. (Class days and times vary)

Duration 1 year; 2 semesters with a final research project

https://www.ncirl.ie/Courses/Course-Details/course/MSCDAD

Careers or further progression

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.

Further enquiries

For Further Information Contact:
The Admissions Team
Telephone: 1850 221 721
Email: admissions@ncirl.ie
Web: www.ncirl.ie

Subjects taught

Year 1-2
Core Modules
• Statistics for Data Analytics
• Data Warehousing and Business Intelligence
• Strategic ICT and e-Business Implementation
• Advanced Data Mining
• Data Visualisation
• Research in Computing
• Research Project or Industry Research Project

In addition, there is a choice of two electives (one in Year 1 Semester 2 and one in Year 2 Semester 1)

Elective Choices
• Data Storage and Management
• Managing the Organisation
• Programming for Data Analytics
• Analytical CRM

Comment

Location: IFSC Campus

Assessment method

Assessment
The course will be assessed with a blend of project work and exams. This varies between modules but typically assessment is 50% continuous assessment and 50% exam.

Please note that in some instances exams may take place in the daytime, evenings and at weekends.

Course fee

Part-time
Fees
€4,475 per annum €8,950 total fee (Fees revised annually)

Full-time
Fees
€6,500 total fee (EU/Ireland applicants)
€12,500 total fee (International)

Enrolment and start dates

Start Date: September 2017

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