| Course Name |
Computing - Big Data Analytics |
| Course Provider |
Letterkenny Institute of Technology |
| Course Code |
LY_KDATA_M |
| Course Type |
Postgraduate |
| Qualifications |
| Award Name | NFQ Classification | Awarding Body | NFQ Level |
| Degree - Masters (Level 9 NFQ)
More info...
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Major |
Letterkenny Institute of Technology |
Level 9 NFQ |
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| Apply To |
Course provider |
| Attendance Options |
Full time, Part time, Daytime |
| Location (Districts) |
Letterkenny |
| Qualification Letters |
MSc |
| Application Date |
Application Deadline - 14 September. |
| Application Weblink |
Web Page - Click Here |
| Duration |
1 year, full-time
2 years, part-time |
| Course Fee |
EU Fees: €5,000.00
Non-EU Fees: €10,000.00 |
| Entry Requirements |
Expand+Minimum Entry Requirements
Level 8 Honours Degree in Computing, or equivalent, second class honours (2.2), or Higher Diploma in Computing (Conversion Course into Computing). Non computing applicants must have a minimum of 30 ECT credits in Computing...
Hide-Minimum Entry Requirements
Level 8 Honours Degree in Computing, or equivalent, second class honours (2.2), or Higher Diploma in Computing (Conversion Course into Computing). Non computing applicants must have a minimum of 30 ECT credits in Computing or Computing related modules, or computer industry experience. If you do not have an honours degree but have relevant experience you may also be eligible to apply via Recognition of Prior Learning (RPL). Applicants may also attend a one week bridging course where necessary.
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| Course Content |
Expand+Is this course for me?
Our Master of Science in Computing in Big Data Analytics is a one year, full-time or two year, part-time programme. It focuses on the processes involved in examining and interpreting large amounts of data of a variety of types...
Hide-Is this course for me?
Our Master of Science in Computing in Big Data Analytics is a one year, full-time or two year, part-time programme. It focuses on the processes involved in examining and interpreting large amounts of data of a variety of types to uncover hidden patterns, unknown correlations and other useful information.
From banking and financial services to retail and healthcare, as well as life sciences, the opportunities in big data analytics are expanding all the time, and this course provides you with excellent qualifications to make the most of the ever increasing opportunities.
After all, your skills can provide competitive advantage for businesses including more effective marketing and increased revenue which is why more and more companies have moved into the field, harnessing talents such as yours to exploit the huge volumes of data now available.
The opportunities for successful graduates exist in companies running large database systems, as well as the payment card industry and financial services. Roles typically include becoming a data storage manager, data analyst or data scientist.
Key features
• Data Analytics are used across all parts of the economy.
• Demand for Data Analysts is growing dramatically
• Flexible part-time and full-time options
• Industry input into course design
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| Subjects Taught |
What will I study?
Semester 1
• Business Intelligence (M)
• Mathematics for
• Analytics (M)
• Big Data Architecture
• (M)
Semester 2
• Machine Learning (E)
• Big Data Analytics (M)
• Secure Information Systems (E)
• Data Science (E)
• Performance Engineering (E)
Semester 3
• Dissertation (M)
(M) = Mandatory, (E) = Elective
Please Note: Students must choose 2 elective modules in Semester 2. Not all electives will necessarily be offered. |
| Careers or Further Progression |
Follow-on Courses
Follow up programmes elsewhere include:
• Level 10 studies (Doctoral) at other institutions and universities at home and abroad.
Career Pathways
The main employers are:
• Companies with Large Database Systems
• Payment Card Industry
• Financial Services
Graduate Careers
Former graduates are employed in the following capacities:
• Data Scientist
• Data Storage Manager
• Data Analyst |
| Further Enquiries |
Further Information
Contact
Thomas Dowling
Head of Department
Email: Thomas.Dowling@lyit.ie
Telephone: +353 (0)74 918 6304 |
| Course Web Page |
Web Page - Click Here |
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