MScData Analytics
| Study location | Ireland, Dublin |
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| Type | Master courses, full-time |
| Nominal duration | 1 year |
| Study language | English |
| Awards | MSc |
| Tuition fee | €15,000 per programme |
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| Entry qualification | Undergraduate diploma (or higher) Applicants will normally hold a level 8 honours degree (min 2.2) (or equivalent) in finance or a cognate field of study. The college operates a Recognition of Prior Experiential Learning (RPEL) scheme meaning applicants who do not meet the normal academic requirements may be considered based on relevant work and other experience. This may be assessed using a written application and/or interview. The entry qualification documents are accepted in the following languages: English. Often you can get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. |
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| Language requirements | English IELTS: 6.0 |
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| Other requirements | Please upload any documents you feel are relevant to your application. All students should upload copies of the following documents: - Your degree certificates / academic transcripts If you submit your application without the required and necessary documentation, It will be unable to process your application until the reception of all relevant documents. |
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| More information |
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Overview
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.
-Formulate and implement a novel research idea using the latest industry practices.
-Demonstrate expert knowledge of data analysis, statistics, and the tools, techniques and technologies of data analytics utilised in both technical and business contexts.
-Critically assess and evaluate business and technical strategies for data analytics.
-Develop and implement effective business and technical solutions for data analytics.
-Critically appreciate ethical and data governance issues relevant to 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 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.
According to a 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.
Programme structure
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.
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.
Assessment
This 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.
Career opportunities
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.