Master of Science in Computing in Big Data Analytics
A postgraduate programme focused on interpreting large-scale data to uncover hidden patterns and correlations.
Best for:Best for computing graduates or professionals seeking to specialize in data analytics and large-scale data interpretation.
Overview
The Master of Science in Computing in Big Data Analytics at ATU Donegal is designed to equip students with the skills necessary to examine and interpret complex, large-scale datasets. The curriculum covers the methodologies required to identify hidden patterns, unknown correlations, and actionable insights across various data types. Students will engage with advanced computational techniques to solve real-world problems through data-driven decision-making. The programme is available as a one-year full-time course or a two-year part-time course, delivered on-campus.
What you'll do
- Engage in advanced study of data examination and interpretation techniques.
- Develop proficiency in identifying hidden patterns and correlations within large datasets.
- Apply computational methods to extract useful information from diverse data sources.
- Complete 90 credits of coursework as required by the programme structure.
- Participate in on-campus academic activities and collaborative projects.
Requirements
Degree required: Level 8 Honours degree in Computing (2.2 grade or higher) or a Higher Diploma in Computing.
Degree offered: MSc
Language: English proficiency is required for all applicants.
Instruction: English
- Foundational knowledge in computing or related modules.
- Ability to meet the 30 ECTS credit requirement in computing for non-computing applicants.
- Analytical mindset for data interpretation.
- Holders of a Level 8 Honours degree in Computing (2.2 or higher).
- Holders of a Higher Diploma in Computing.
- Non-computing graduates with at least 30 ECTS credits in computing modules or equivalent industry experience.
- Applicants without an Honours degree may be considered via Recognition of Prior Learning (RPL).
Funding & terms
Programme and admissions
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- Intake
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- Prerequisites
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How to apply
Applications for the September intake typically open in February, while January intake applications open in October. Interested candidates should visit the official university course webpage to confirm specific closing dates and submit their application through the university portal.
- Academic transcripts
- Proof of prior learning (if applicable)
- Evidence of computing credits or industry experience
Contact
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