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Masters
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Computer Science & IT
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Big Data and Business Intelligence
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MASTERS

Big Data and Business Intelligence

University of Greenwich
LondonUK
On campus
Full-time
Duration
1 Year
Language
English
Apply date
May 2024
Start date
Sep 2024

Program Description

This innovative master's course provides you with the skills to contribute to the design and development of big data systems as well as distributed / internet-enabled decision support application software systems.

We focus on modern engineering methods, tools and techniques, including data analytics, machine learning, business intelligence, data mining. You will also have the opportunity to learn programming languages such as Hadoop, Python, and R. Our software engineering approach to building applications helps you to develop a life-cycle view of software development.

Drawing on our research excellence in this area, this innovative course in big data and business intelligence is designed to give you a competitive advantage in this fast-growing business domain.

Notes:

• Tuition fees for students who have citizens' rights after Brexit: £10,500

Entry Requirements

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Curriculum

Core Modules

MSc Project (60 credits)

Big Data (15 credits)

Advanced Database Technologies (15 credits)

Applied Machine Learning (15 credits)

Programming Fundamentals for Data Science (15 credits)

Graph and Modern Databases (15 credits)

Data Warehousing and Business Intelligence (15 credits)

Essential Professional and Academic Skills for Masters Students

Optional Modules

Students are required to choose 15 credits from this list of options:

Software Tools and Techniques (15 credits)
User Centred Web Engineering (15 credits)
Clouds, Grids and Virtualisation (15 credits)

Students are required to choose 15 credits from this list of options:

Systems Modelling (15 credits)
Data Visualisation (15 credits)

Careers

Graduates from the MSc Big Data and Business Intelligence course are equipped for employment in industry, commerce or research with a proficiency in the key theoretical and practical areas of big data systems development.

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