Big data is increasingly important in today’s commercial landscape. As a data scientist specialising in big data, you’ll help companies make sense of large amounts of structured and unstructured data, providing rapid insights that enable them to make better, quicker decisions.
As a graduate in Big Data you’ll be able to work in a wide range of sectors such as digital technologies, energy and utilities, financial services, public sector and healthcare.
A minimum of a second class honours degree or equivalent in a numerate subject such as maths, computing, engineering or an analytic science.
Applicants without these formal qualifications but with significant appropriate work experience are encouraged to apply.
English language requirements
If English is not your first language, you must have one of the following qualifications as evidence of your English language skills:
- IELTS: 6.0 with 5.5 minimum in each skill
- Cambridge Certificate of Proficiency in English (CPE): Grade C
- Cambridge Certificate of Advanced English (CAE): Grade C
- Pearson Test of English (Academic): 54 with 51 in each component
- IBT TOEFL: 80 with no subtest less than 17
The MSc Big Data course is delivered over one year.
Modules
The module details given below are subject to change as the University regularly revises and refreshes the curriculum of our taught programmes. The modules outlined below represent those offered in 2018/19 on this course of study.
- One-time fee Amount in AED
- Registration 3,500
- Annual fee Amount in AED (per year)
- Tuition 50,000
- Examination 1,000
Big data skills are in high demand. You will have opportunities with data-driven companies from a wide variety of sectors and command a salary that’s typically higher than the IT average. As a graduate in Big Data you’ll be able to work in a wide range of sectors, such as digital technologies, energy and utilities, financial services, public sector and healthcare.
A degree in Big Data opens many career paths in different sectors:
• Banking and Finance
• Data Driven Marketing
• Sport and Fitness
• Health and Medicine
• Engineering
• Data Journalism
• Mapping and GIS
• New Media
