| Program start date | Application deadline |
| 2024-01-01 | - |
| 2024-09-01 | - |
| 2025-01-09 | - |
| 2025-01-22 | - |
| 2025-09-14 | - |
| 2025-01-03 | - |
| 2024-09-17 | - |
| 2025-09-01 | - |
| 2024-06-01 | - |
| 2024-11-06 | - |
| 2024-01-06 | - |
| 2025-01-01 | - |
| 2024-09-06 | - |
| 2025-01-06 | - |
| 2025-09-06 | - |
Program Overview
This MSc in Big Data Technologies equips students with the knowledge and skills to understand and utilize big data systems architectures. Its core modules cover big data theory, data repositories, data warehousing, data mining, and machine learning. Optional modules allow students to specialize in areas such as data visualization, web analytics, cyber security, and business analytics. The program prepares graduates for careers in AI, analytics, data analysis, and other roles in the big data industry.
Program Outline
Degree Overview:
This MSc in Big Data Technologies is designed for individuals seeking to enter the rapidly expanding field of big data. The program aims to equip students with the knowledge and skills necessary to understand and utilize big data systems architectures. It focuses on providing practical, hands-on experience with industry-standard software and technologies. The program is suitable for recent graduates seeking a higher qualification or technical skills in big data, as well as professionals looking to update their knowledge in this field.
Outline:
Students learn about technologies used in big data projects, including SQL and NoSQL databases, Hadoop, MapReduce, and Hive. It covers practical aspects of data modeling, database design, and introduces the features and constructs of SQL. Students learn how to build data warehouses, understand their structures, and the concept of multi-dimensional modeling.
- MSc Project: This module consolidates and extends the knowledge acquired in the taught portion of the course. Students undertake a comprehensive individual project on an approved topic related to their studies, involving research, planning, critical evaluation, and reflection activities. The module includes blended learning workshops to provide foundational knowledge for project development. Tools like R and Tableau are used to prepare students for becoming data visualization specialists.
- Web and Social Media Analytics: This module explores the use of modeling to analyze and measure online presence and impact using web and social media data. The module aims to equip students with the skills and knowledge for a career in web or social media marketing. It covers developments in automated threats and countermeasures.
- Business Analytics: This module equips students with foundational knowledge in statistics, optimization modeling, and operational research to enable data-driven business decision-making. Students gain essential concepts in descriptive, predictive, and prescriptive analytics, applying these techniques to real-world business problems. They analyze risk and uncertainty, evaluate analytical methods, interpret results, and communicate insights through effective writing and visualization.
Assessment:
Assessment methods typically include practical assessments like presentations, podcasts, and blogs, as well as coursework such as essays, in-class tests, portfolios, and a dissertation.
Teaching:
Teaching methods include lectures, tutorials, seminars, and practical/hands-on sessions. Students learn through coursework, class presentations, group work, and the use of industry-standard software such as R, Python, MySQL, Oracle, and NoSQL databases.
Careers:
The program prepares students for roles such as:
- AI and analytics consultant
- Application/system developer
- Architect, designer, and administrator of data systems
- Big data engineer/consultant
- Business intelligence analyst/consultant/developer
- Credit risk engineer
- Data analyst
- Data governance analyst/officer
- Data manager
- Data mining and business intelligence specialist
- Data quality/compliance officer
- Data officer
- Data scientist
- Database/web application developer
- ETL developer/programmer
- OLAP programmer
Other:
- The program is accredited by BCS, the Chartered Institute for IT, for the purposes of partially meeting the further learning academic requirement for registration as a Chartered IT Professional.
- The program is based at the Cavendish Campus in central London, a major tech hub.
- The program provides access to free online courses in Adobe and Microsoft Office applications, as well as thousands of specialist courses on LinkedIn Learning.
UK Fees:
£10,500
International Fees:
£17,000
University of Westminster
Overview:
University of Westminster is a public university located in London, England. It offers a wide range of undergraduate and postgraduate programs across various disciplines. The university is known for its focus on practical learning and its strong connections to the industry.
Services Offered:
Student Life and Campus Experience:
The university has four campuses across London, providing students with a vibrant and diverse campus experience. Students have access to various facilities, including a cinema, gallery spaces, and sports facilities. The university also offers a range of student support services, including career guidance, academic support, and mental health services.
Key Reasons to Study There:
Location:
The university's location in London provides students with access to a wealth of cultural and professional opportunities.Practical Learning:
The university emphasizes practical learning, with many programs incorporating work placements and industry projects.Industry Connections:
The university has strong connections to industry, providing students with opportunities for networking and career development.Diverse Student Body:
The university has a diverse student body, creating a welcoming and inclusive environment.Academic Programs:
The university offers a wide range of academic programs, including:
Undergraduate courses:
A broad range of undergraduate courses in various disciplines, including business, design, creative industries, and liberal arts.Postgraduate courses:
A variety of postgraduate study options, including master's degrees, research degrees, and short courses.Other:
The university has a strong commitment to research and innovation, with a focus on areas such as sustainability, social justice, and digital technologies. It also has a dedicated alumni network, providing support and opportunities for graduates.
Entry Requirements:
A minimum of a lower second class honours degree (2:2) in IT or computing discipline, or in another discipline that either provides important underpinning for or insight into IT and computing, or it is closely related to it (e.g. sciences or engineering, business studies). If you do not have the required formal qualifications, you may be considered if you are already in employment and your role involves the use or support of the data modelling techniques and technologies covered in the course.
