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University of Westminster, London: Data Science and Analytics
| Institution | University of Westminster, London View institution profile |
|---|---|
| Department | School of Computer Science and Engineering View department profile |
| Web | https://www.westminster.ac.uk |
| Study type | Taught |
Summary
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'll 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'll 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 coursework, class presentations, group research work, and the use of a range of industry-standard software such as R, Python, Simul8, Palisade Decision Tools, Tableau, and Oracle.
Modules are typically assessed through practical coursework, which may also include an in-class test.
MSc
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course. If your first language is not English you should have an IELTS 6.5 with no element below 6.0. |
| Location | 115 New Cavendish Street 115 New Cavendish Street Westminster W1W 6UW |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course. If your first language is not English you should have an IELTS 6.5 with no element below 6.0. |
| Location | 115 New Cavendish Street 115 New Cavendish Street Westminster W1W 6UW |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course. If your first language is not English you should have an IELTS 6.5 with no element below 6.0. |
| Location | 115 New Cavendish Street 115 New Cavendish Street Westminster W1W 6UW |
| Level | RQF Level 7 |
|---|---|
| Entry requirements | A minimum of a lower second class honours degree (2:2) in a scientific or engineering discipline with some exposure to the use of IT, or in an area of computer science or IT with a strong interest in quantitative analysis. If you do not have a formal qualification, but you are already in employment, you may be considered if your role involves the data mining and decision support techniques and technologies deployed in the course. If your first language is not English you should have an IELTS 6.5 with no element below 6.0. |
| Location | 115 New Cavendish Street 115 New Cavendish Street Westminster W1W 6UW |
At the University of Westminster, our postgraduate courses in media, fashion, art, computer science and engineering are designed for ambitious professionals ready to advance their careers. Shaped by London’s global creative and tech industries, our programmes cover media, art, fashion, design, business, immersive technologies, cybersecurity, data science, and artificial intelligence.
You’ll learn from experienced practitioners and active researchers who bring real-world insight directly into the classroom. Through live briefs, collaborative projects, professional practice modules, and opportunities to exhibit, screen, or publish work, you’ll gain advanced theoretical knowledge alongside practical skills, critical thinking, and professional development, preparing you to thrive …
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