Master of Science Big Data Analytics

Full Time / Part-time

Master of Science Big Data Analytics

Letterkenny Institute of Technology
  • $ See Details
    1st year fees
  • Unkown
    CREDITS
  • Campus
    BASED
  • Masters
    DEGREE
  • 1 - 2 years
    DURATION

Introduction

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.

Admission 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.

Courses Units

You need to complete credit hours to successfully obtain this degree. Please check detail of study units at https://www.lyit.ie/CourseDetails/D202/LY_KDATA_M/BigDataAnalytics

More Information

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.

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