Program Overview

About this Course

The Data Science for Health (Conversion) MSc is designed as a conversion course, welcoming students from diverse academic and professional backgrounds. This programme equips graduates from various fields with the technical and analytical skills needed to thrive in the rapidly growing health data science sector.

Introduction

This MSc is suitable for students who hold a 2.2 degree from a UK university (or equivalent) in any subject, as the programme will train students in basic statistical and computing skills. For overseas students, an acceptable English language qualification is required, with an IELTS score of 6.5 or equivalent, and no individual band less than 6.0.

What You'll Learn

• The importance of data science to healthcare
• The role of a health data scientist as a member of a healthcare team
• In-depth knowledge and systematic understanding of the ethical, legal, and regulatory frameworks impacting health data science
• A broad base of knowledge, enabling students to apply statistical and machine learning approaches to analyze health-related data and critically evaluate findings
• Professional skills, including team science communication skills, to work successfully as a data scientist in the public or private sector
• The opportunity to obtain specialized knowledge along a statistics track, computer science track, or a combination of both

Course Content

The programme blends core principles of computer science with advanced statistical analysis and data visualization techniques, demonstrating how health data science can enhance our understanding of disease and healthcare.

Semester One

• Compulsory modules:
  • Introduction to Health Data Science (DASC501) - 15 credits
  • Statistics for Health Research (DASC502) - 15 credits
  • Computer Programming for Health Research (DASC509) - 15 credits
• Optional modules:
  • Using Routine Data for Public Health (DASC503) - 15 credits
  • An Introduction to Qualitative Research (PUBH160) - 15 credits
  • Artificial Intelligence and Machine Learning for Health (DASC512) - 15 credits

Semester Two

• Optional modules:
  • Evaluation of Healthcare Interventions (DASC504) - 15 credits
  • Prediction Modelling & Joint Longitudinal and Survival Data Analysis (DASC506) - 15 credits
  • High-Dimensional Data Structures and Learning Algorithms (DASC507) - 15 credits
  • Statistical Genetics and Pharmacogenomics (DASC508) - 15 credits
  • Data Mining and Visualization (COMP527) - 15 credits
  • Machine Learning and Bioinspired Optimization (COMP532) - 15 credits
  • Computational Intelligence (COMP575) - 15 credits
  • Actionable Healthcare Data Analytics (DASC505) - 15 credits

Dissertation

• Compulsory module:
  • Dissertation (DASC500) - 60 credits

Teaching and Assessment

The learning and teaching strategy for the programme comprises a mixture of formal lectures, practical and tutorial sessions, discussion groups, student-centered learning, and project work. Each module (except the dissertation) is worth 15 credits and totals approximately 150 hours, with 25-50 of those hours in taught sessions.

Assessment

Assessments vary by module and include written articles, data analysis, posters, presentations, and exams.

Course Options

Studying with the University of Liverpool means you can tailor your degree to suit you. This includes the option to study some modules as standalone Continuing Professional Development (CPD) modules or to undertake the programme as an intercalated degree.

Your Experience

Each day will involve a series of interesting, research-focused lectures and practical sessions, with time to digest content and prepare for later sessions and assessments. The University of Liverpool provides a supportive learning environment, ensuring all students develop the necessary skills to succeed.

Careers and Employability

Graduates in data science are in high demand worldwide. This programme provides the tools to help students succeed, whether they aspire to work as a data scientist in the NHS, develop AI-driven healthcare solutions, or contribute to groundbreaking medical research. Career opportunities include roles such as PhD student, Research Assistant, Trial Statistician, Epidemiologist, and Data Scientist.

Fees and Funding

Tuition Fees

• UK fees: £14,000 per year (full-time)
• International fees: £32,000 per year (full-time)

Additional Costs

Students should budget for additional costs such as buying a laptop, books, or stationery.

Scholarships and Bursaries

The University of Liverpool offers a range of scholarships and bursaries that could help pay tuition and living expenses. Examples include The Salters' Fellowship, Bracken Scholarship, and John Lennon Memorial Scholarship.

Entry Requirements

Postgraduate Entry Requirements

This master's programme is suitable for students who hold a 2.2 degree from a UK university (or equivalent) in any subject.

International Qualifications

Applicants with any academic background will be considered, as students will be trained on basic statistical and computing skills. An acceptable English language qualification (IELTS 6.5 or equivalent, with no band less than 6.0) is required.

English Language Requirements

Students must demonstrate competence in the use of English language, unless they are from a majority English-speaking country. The University accepts various international language tests and country-specific qualifications.

Pre-sessional English

For students who do not meet the English language requirements, the University offers Pre-sessional English courses to help students achieve the required level. The length of the Pre-sessional English course depends on the student's current level of English language ability.