MSc Big Data and Business Intelligence

at University of Greenwich

• The core modules cover fundamental topics such as big data analytics, data mining, database systems, and business intelligence tools. 
• Students gain hands-on experience with programming languages and software used for handling and analysing large data sets. 
• There are opportunities to study advanced subjects like machine learning, data visualisation, and cloud computing through elective modules.
•  The programme incorporates case studies and projects that allow students to apply their knowledge to real-world scenarios. 
• The dissertation project enables students to conduct independent research on a specific area of big data or business intelligence.

Course Modules

• MSc Project 
• Big Data 
• Advanced Database Technologies 
• Applied Machine Learning 
• Programming Fundamentals for Data Science 
• Graph and Modern Databases 
• Data Warehousing and Business Intelligence 
• Essential Professional and Academic Skills for Masters Students

Important Dates

Intake schedules at the university fluctuate based on the program and campus. It's advisable for prospective students to refer to the university's official website or connect with the admissions office for the most recent updates regarding 2024 intake periods. Though universities generally enrol students in the autumn (September/October) and spring (January/February) semesters, it's vital to validate the precise details directly from the institution.

• An applicant should hold a bachelor's degree with honours, attaining a classification of 2:2 or higher, in a field related to computing or in a relevant numerical discipline (such as mathematics, physics, engineering, information systems, or multimedia), that incorporates experience in software development.
• Individuals undertaking the IELTS Academic examination should aim for an overall score of 6.0, ensuring that none of their section scores drop below 5.5.

International Tuition Fees:

£18150 per year

Graduates of this programme are well-equipped to pursue exciting careers in the rapidly growing field of data science and analytics. Potential roles include data analyst, data scientist, business intelligence analyst, big data engineer, data architect, and machine learning engineer.