Health Data Science MSc

Start date
January 2023, September 2023
Duration
1 year full-time (Sep 2023), 2 years part-time (Sep 2023), 18 months part-time (Jan 2023)
Campus
Dubai
Course Type
Postgraduate, Taught
Fees

Annual tuition fee for 2023/24:
AED 125,869 (full-time)

Scholarships available for all students up to 40%

 

This Masters programme is aimed at graduates with interests in artificial intelligence, health data and advanced computational approaches in the clinical and biomedical space. It will equip future health data scientists with the knowledge and skills to perform analyses and develop novel tools and methods for this rapidly growing field.

Subject to Ministry of Education accreditation

It is aimed at students with diverse backgrounds from biomedical/medical domains, including clinical trainees, as well as computer science, mathematics and statistics to conduct their own analyses, and also to create the next generation of cutting-edge health data scientists who will be able to develop new tools and methods matching the latest technological advancements.

You will learn about the breadth of health data science and its applications, and you will be taught how to design, perform and enhance analyses with the appropriate methods and technologies to address practical medical and clinical questions. You will also benefit from training in areas such as clinical bioinformatics, health informatics, epidemiology, clinical systems, integrated multimodal data analysis, bioinformatics and omics analytics for health data science careers in academia, industry and national health services.

Programme lead

Dr Marc Haber

Marc Haber profile picture

Dr Haber is an Associate Professor at the Institute of Cancer and Genomic Sciences and the Centre for Computational Biology. His group investigates genetic variation in humans to explain the differences between populations in disease incidence and progression; and focuses on genetically underrepresented populations to understand how their genomic history has contributed to their disease burden. 

Dr Haber’s background is in population genetics. He uses sequencing data from modern and ancient populations to learn about the events that shaped the human genome; this involves investigating how humans migrated and spread around the world, mixed, and adapted to new environments and the consequence of these events on disease and phenotype.

View Dr Haber's staff profile. 

I would recommend this course to anyone who wants to embrace and start their journey into data science.

MSc Health Data Science student

Why study this course?

The MSc Health Data Science will allow you to:

  • be embedded within a diverse, collaborative, interdisciplinary environment, incorporating academia, industry and healthcare.
  • acquire skills in governing health data science, its foundations and effective application within healthcare settings.
  • develop an in-depth understanding of healthcare systems, their underlying ethics and their governance structures. Students will also explore the role of current and potential future applications of health data science in the delivery of patient-centred care, patient-provider interactions and wider aspects of healthcare delivery.
  • understand how health data science skills can revolutionise healthcare data and patient-specific genome information for research, clinical care and innovation in the 21st century.
  • learn the value of different types of health information, systems and integration, and the role of information related technologies in delivering healthcare.
  • gain practical experience of working within diverse, multi-disciplinary environments across the healthcare sector and its associated industries, and develop effective communication and delivery skills within the wider landscape.
  • enhance their prospects. 80% of MSc Health Data Science students have received an offer for a PhD or job before finishing their thesis (2022).

Modules

Please note: The modules listed on the website for this programme are regularly reviewed to ensure they are up-to-date and informed by the latest research and teaching methods. The modules listed below are those currently intended for students starting in 2022. Please ensure you review these modules for updates before applying for this programme.

  • Foundations of Computing Practices in Health Data Science (20 credits)
  • Essentials of Mathematics and Statistics (20 credits)
  • Data Analytics & Statistical Machine Learning (20 credits)
  • Health Data Fundamentals (20 credits)
  • Epidemiology and Health Informatics (20 credits)
  • Integrative Multimodal Data Analytics (20 credits)
  • Interdisciplinary Health Data Research Project (60 credits)

Fees

We charge an annual tuition fee for 2023 entry:

  • Full-time: AED 125,869 
  • 18 months part-time: AED 62,935 (per year)
  • 2 years part-time: AED 62,935 (per year)

Scholarships

We have a number of scholarships available.

Scholarship information

How To Apply

To find out more about our application process please visit our how to apply page before starting your application.

Our Standard Requirements

A 2:1 undergraduate honours degree in a medical/life science (medicine, biology, chemistry, etc.) or quantitative science subject (computer science, mathematics, physics, etc.). Equivalent relevant work experience will also be considered for eligibility to enter the programme.

International students

Academic requirements

We accept a range of international qualifications - use the dropdown box below to select your country and see the equivalencies to the above UK requirements.

English language requirements

IELTS 6.5 with no less than 6.0 in any band.

If you are made an offer of a place to study and you do not already meet the language requirement, you have the option to enrol on our English for Academic Purposes Presessional Course. If you successfully complete this, you will be able to fulfil the language requirement without needing to take a further qualification.

International Requirements


Course delivery:

Full-time students will typically take three modules in each semester, followed by a dissertation.

The modules are delivered in block-teaching style (between 2-3 weeks) and students can be expected to require 10-15 hours of classroom time per week. Part-time students will typically take three modules across each year, followed by a dissertation for MSc students.

Each module represents a total of 200 hours of study time, including preparatory reading, self-guided study and assignment preparation.

Assessment Methods

You will be assessed through a variety of methods, including essays, exams, oral presentations, computer-based problem solving exercises and a thesis.

This programme will give you clear and compelling experience of working across academic, healthcare and industry sectors, with extensive supervisory and mentoring arrangements to maximise your exposure to these environments. Not only will this prepare you mentally and practically, it will also help identify specific opportunities and contacts for progress into relevant career pathways. 80% of MSc Health Data Science students have a PhD or job offer before finishing their thesis (2022). 

Careers Service

During your studies you will have access to a wide range of dedicated support, helping you to achieve your career goals. These include:

  • Individual careers advice from the International Careers Consultant and specialist careers advisers, who will be able to answer your requests for advice and guidance
  • Apply Yourself coaching workshops and online tutorials to help you present yourself effectively to employers and recruiters and develop an effective CV
  • Practical help with preparing for interviews and attending assessment centres Access to global job opportunities online and job search webinars
  • Opportunities to network with alumni and potential employers
  • Access to a range of careers information online to help you consider your next stage after your degree and develop an individual career action plan

By making the most of the wide range of services available, you will be able to develop your career from the moment you arrive.