Msc Data Science

at Liverpool Hope University

• The programme begins with core programming, statistics, data mining, and machine learning modules.
•  It then moves into more advanced data science topics like big data analytics, predictive modelling, and visualisation.
•  Students also study databases, data ethics and governance, and research methods. 
• Toward the end, they choose elective modules aligned with their interests and career goals. 
• The degree culminates in a research dissertation project where students apply their data science skills to a real-world problem.

Course Modules

• Data Analytics
• Numerical Methods
• Theoretical Computer Science
• Programming
• Applied Computer Science

Important Dates

Applicants should keep themselves updated by consistently monitoring the university website for any changes in application status. The website will indicate when applications will reopen. Students must ensure they have their required documents ready and not delayed. Seeking assistance from UniScholars to begin the application process can also be advantageous.

• Applicants must possess at least a Second-Class Honours undergraduate degree from a UK university in a related field such as Data Science, Computer Science, Computing, Science, or an engineering discipline, or hold an equivalent higher education qualification.
• For admission, postgraduate applicants must showcase their English language abilities through an IELTS test. A minimum overall band score of 6.5 and a score of at least 6.0 in each sub-skill (Reading, Writing, Listening, and Speaking) are required.

Liverpool Hope University charges between £ 13,000/Yr to £ 16,000/Yr as tuition fees for the MSc Data Science programme. Students are encouraged to frequently check the university's website to stay up-to-date on any potential changes or revisions to the programme fees.

Graduates of this programme are well-positioned for in-demand roles like data scientist, data analyst, machine learning engineer, and business intelligence analyst across industries. Their expertise in statistics, programming, modelling, and working with large datasets allows them to find opportunities in fields like finance, healthcare, marketing, logistics, and more.