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Big Data Analytics (Online) at University of Liverpool - UCAS

There are other course options available which may have a different vacancy status or entry requirements – view the full list of options

Course summary

Further your computer science career with a specialist postgraduate degree in big data analytics. This online master’s programme has been designed to equip students 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. 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. To achieve a full master’s degree, you will be required to complete 180 credits. This programme is also available as a postgraduate diploma (PG Dip) which amounts to 120 credits and a postgraduate certificate (PG Cert) which amounts to 60 credits. Students who complete the PG Cert and PG Dip will have the opportunity to progress to a full master’s degree.   The programme is accredited by the BCS, The Chartered Institute for IT, for the purposes of meeting the further learning academic requirement for registration as a Chartered IT Professional. Teaching methods and style  This programme is designed to be studied wholly online and part-time. Teaching is delivered through our state-of-the-art Virtual Learning Environment (VLE), which provides students with access to all resources required for interactive study online. On this platform, you will be encouraged to work collaboratively with classmates and actively read around your topic through our comprehensive library of eBooks and journals.   Methods of assessment  Assessment is exclusively through online assignments rather than examinations. You will be assessed through a range of activities, including written assignments, presentations, discussion forum participation and journal entries.  Career destinations  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.

Modules

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) Elective module: 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)

Assessment method

Assessment is exclusively through online assignments rather than examinations. You will be assessed through a range of activities, including written assignments, presentations, discussion forum participation and journal entries.


How to apply

International applicants

International applicants may be eligible for a range of scholarships of up to 20%. To learn if you are eligible, contact our admissions team on our website.

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 the eligible countries on our website.


Fees and funding

Tuition fees

EU £16868* Whole course
International £16868* Whole course
England £16868* Whole course
Northern Ireland £16868* Whole course
Scotland £16868* Whole course
Wales £16868* Whole course
Channel Islands £16868* Whole course
Republic of Ireland £16868* Whole course

*This is a provisional fee and subject to change.

Tuition fee status depends on a number of criteria and varies according to where in the UK you will study. For further guidance on the criteria for home or overseas tuition fees, please refer to the UKCISA website .

Additional fee information

No additional fees or cost information has been supplied for this course, please contact the provider directly.
Big Data Analytics (Online) at University of Liverpool - UCAS