Master of Science in Data Science and Analytics

at University of Westminster - Cavendish Campus United Kingdom

Overview

This course (previously Business Intelligence and Analytics MSc) addresses the need to propel information-gathering and data organisation, and exploit potential information and knowledge hidden in routinely collected data to improve decision-making. The course stretches the artificial intelligence (AI), machine learning (ML) and decision science themes to Business Intelligence, Data Science and Business Analytics.

You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, using applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within Data Science, Business Intelligence and Analytics, and how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods for data science. These include data warehousing and mining, distributed data management, and the technologies, architectures, and appropriate AI and ML techniques. The second theme will enhance your knowledge of algorithms and the quantitative techniques including AI, ML, and Operational Research (OR) suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

Teaching approaches include lectures, tutorials, seminars, and practical sessions. You will also learn through extensive course work, class presentations, group research work, and the use of a range of industry standard software such as R, Python, Simul8, Palisade Decision Tools, Hadoop, and Oracle.

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30

Application Processing Days

Under Graduate

Program Level

Fact & Figures

Full Time On Campus

Study Mode

12

Duration

University of Westminster - Cavendish Campus

Location

Master of Science in Data Science and Analytics Assistant Fee

$14000

Tuition Fee

$0

Average Cost of Living

$0

Application Fee

Master of Science in Data Science and Analytics Admissions Requirements

  • Minimum Level of Education Required: To be accepted for this program, students must have a Bachelor's degree.
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Where would you like to study*

Work Permit United Kingdom

There are various options through which a student can get a post study work visa in the UK. 
Tier 1 Graduate Entrepreneur Visa for the graduates with a genuine and credible business idea. 
Tier 2 (General) is the leading immigration visa to work in the UK.
Tier 4 Doctorate Extension Scheme is for students who have completed their Ph.D. and is valid for 12 months for them to work, look for work or set up a business. 
Tier 5 Youth Mobility is for individuals of certain countries like Australia, Canada, Japan, Monaco, Hong Kong, South Korea, Taiwan, and New Zealand aged between 18 -30 who wish to move to the UK. 
Tier 5 GAE is for individuals who want to come to the UK for work experience, training, research or a fellowship. 
UK Ancestry is for individuals who are a citizen of a commonwealth and plan to work in the UK and have a grandparent who was born in the UK.
 

Detailed Program and Facts

30

Application Processing Days

Full Time On Campus

Program Intensity

Under Graduate

Program Level

12

Duration

Study Visa

English Test Requirement

6.5

Minimum Overall Score

6.0

Minimum Writing

88.0

Minimum Overall Score

59.0

Minimum Overall Score

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You will focus on developing solutions to real-world problems associated with the changing nature of IT infrastructure and increasing volumes of data, using applications and case studies, while gaining a deep appreciation of the underlying models and techniques. You will also gain a greater understanding of the impact technological advances have on nature and practices adopted within Data Science, Business Intelligence and Analytics, and how to adapt to these changes.

Embedded into the course are two key themes. The first will help you to develop your skills in the use and application of various technologies, architectures, techniques, tools, and methods for data science. These include data warehousing and mining, distributed data management, and the technologies, architectures, and appropriate AI and ML techniques. The second theme will enhance your knowledge of algorithms and the quantitative techniques including AI, ML, and Operational Research (OR) suitable for analysing and mining data and developing decision models in a broad range of application areas. The project consolidates the taught subjects covered, while giving you the opportunity to pursue in-depth study in your chosen area.

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