Big Data Analytics

Big Data Analytics MSc follows a career-driven curriculum, developed to provide practical skills and knowledge directly applicable to a workplace. You will have the opportunity to gain a comprehensive understanding of both the technology that supports big data analytics and the practical application of this technology in the context of business information and real-world problems.

Throughout your studies, you will gain a critical understanding of the challenges that private and public enterprises face with respect to the practical adoption of big data analytics within the modern workplace. You will also dive into the technical and managerial end-to-end challenges associated with the storing, processing, visualisation, and mining of large disparate data collections.

Learning is conducted in a research-focused environment that aims to engage in collaborative enquiry with other students with a focus on applying your knowledge and skills to practical problems.

Paid course type

Further your computer science career with a specialist postgraduate degree in big data analytics, accredited by the BCS, The Chartered Institute for IT. You will graduate with expertise in an area of computing that has seen recent and rapid growth, and in which there is expected to be a significant skills shortage.  

Course details

This MSc consists of the following modules and is available as a postgraduate diploma (PG Dip) which amounts to 120 credits and a postgraduate certificate (PG Cert) which amounts to 60 credits.

  • Global Trends in Computer Science (15 credits)
  • Data Visualisation and Warehousing (15 credits)
  • Machine Learning in Practice (15 credits)
  • Cloud Computing (15 credits)
  • Security Engineering and Compliance (15 credits)
  • Deep Learning (15 credits)
  • Electives: choose one:
    • Applied Cryptography (15 credits)
    • Cyber Forensics (15 credits)
    • Cybercrime Prevention and Protection (15 credits)
    • Information Technology Leadership (15 credits)
    • Multi-Agent Systems (15 credits)
    • Natural Language Processing and Understanding (15 credits)
    • Reasoning and Intelligent Systems (15 credits)
    • Robotics (15 credits)
    • Security Risk Management (15 credits)
    • Strategic Technology Management (15 credits)
    • Technology, Innovation and Change Management (15 credits)
  • Research Methods in Computer Science (15 credits)
  • Computer Science Capstone Project (60 credits)


Entry requirements

All applications will be considered on a case-by-case basis. If you want to discuss your previous qualifications and experience before applying, please contact our admissions team.

Applicants should possess either: 
•    A minimum of a 2:2 class degree in Computer Science or a closely related subject, equivalent to a UK bachelor’s degree, coupled with two years’ experience in employment; or
•    Professional work experience and/or other prior qualifications, which will be considered on a case-by-case basis.

All applicants must provide evidence that they have an English language ability equivalent to an IELTS (academic) score of 6.5.

If you don’t have an IELTS or equivalent certificate, you can take our free online English test to assess your proficiency. You don’t need to prove your English ability if you are a national of, or have completed a qualification equivalent to a UK degree in, any of these countries.

Career outcomes

The programme follows a career-driven curriculum, developed by industry leaders and experts to ensure the taught skills and knowledge are directly applicable to a workplace. Graduates will be able to successfully apply their newly acquired skills and knowledge in demanding roles within a range of sectors. Potential job titles include Data Scientist, Big Data Consultant, Machine Learning Engineer and Research Scientist.

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Institution Address
University of Liverpool, Liverpool L69 3BX, United Kingdom
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+44 (0)151 318 4466
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