Masters in Clinical Data Science

This programme, supported by Health Data Research UK (HDR UK), aims to train a new generation of world-leading health data scientists, to work in both the public and private sector. Teaching will focus on building strong quantitative,  computational and practical data management skills, while providing opportunities to develop key professional skills required to be a successful health data scientist.

The MSc Clinical Data Science programme has been developed in response to an identified gap in data science skills in the NHS. It is designed to be relevant to you whether you are new to data science or experienced in this field, and whether your career is in healthcare, medical research or public health.

This programme will equip graduates with the skills and tools required for analysing and managing large, diverse datasets across healthcare systems. Working with multinational, multidisciplinary teams, you’ll be able to harness the power of modern computing to solve big data challenges in healthcare – from clinical trials to real-world registries – and train as a future leader of data science in industry and academia. The programme is offered through a collaboration between Imperial College London and the National Health Service (NHS) at Imperial College Healthcare NHS Trust, which will provide direct access to enormous hospital-based data sources.

The programme will enable you to:

  • apply statistical and machine learning approaches to analyse health-related data
  • acquire the tools and skills to manage very large diverse datasets across healthcare systems
  • develop the professional skills – including teamwork, project management, and presentation skills – to work as a successful data scientist in the public or private sector
  • understand the varied roles of a health data scientist within the wider health and health research environment
  • learn about the key sources of health data, and the context in which these data are collected, implications of the context on issues such as data quality, accessibility, bias and the appropriateness of use to address specific questions
  • study the key issues related to ethics, security and information governance

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Masters In Clinical Data Science

The programme

This programme, supported by Health Data Research UK (HDR UK), aims to train a new generation of world-leading health data scientists, to work in both the public and private sector. Teaching will focus on building strong quantitative,  computational and practical data management skills, while providing opportunities to develop key professional skills required to be a successful health data scientist.

Health Data Science is an emerging discipline, combining mathematics, statistics, epidemiology and informatics. This programme will equip graduates with the tools and skills to manage and analyse very large diverse datasets across healthcare systems.

The programme will enable you to:

  • apply statistical and machine learning approaches to analyse health-related data
     
  • acquire the tools and skills to manage very large diverse datasets across healthcare systems
     
  • develop the professional skills – including teamwork, project management, and presentation skills – to work as a successful data scientist in the public or private sector
     
  • understand the varied roles of a health data scientist within the wider health and health research environment
     
  • learn about the key sources of health data, and the context in which these data are collected, implications of the context on issues such as data quality, accessibility, bias and the appropriateness of use to address specific questions
     
  • study the key issues related to ethics, security and information governance.

Funding opportunities 2021-22

Six studentships will be awarded to “Home students” for the 2021-22 MSc Health Data Research programme. Deadline to apply is 31 May 2021.

Three awards will cover:

  • Tuition fees at the Home (UK) full-time fee rate for 1 year, and
  • A tax-free stipend of GBP 16,000 (including London Weighting)

Three awards will cover:

  • 50% of tuition fees at the Home (UK) full-time fee rate for 1 year

master of health data science

MSc Health Data Science Programs

Health data science is a growing field that incorporates health informatics, data science, analytics, and computational modeling to assess large volumes of data from clinical trials, electronic medical records, genetic and genomic epidemiology and environmental health, or health care claims. The analysis of these datasets can help solve problems in public health or biomedical sciences.

The Master of Science (SM) in Health Data Science provides students with the rigorous quantitative training and essential computing skills needed to manage and analyze health science data in order to address important questions in public health, medicine, and basic biology.

Offered by the Department of Biostatistics, this new 60-credit program is designed to provide participants with the knowledge base and targeted skills required for rigorous work in health related data science. Students will learn to:

  • Critically explore, analyze and interpret data
  • Appropriately apply statistical inference to make scientific conclusions from data
  • Understand and employ linear models, regression and matrix algebra
  • Apply methods for high-dimensional data
  • Implement machine learning algorithms
  • Develop and write software
  • Communicate and disseminate results via reproducible reports
  • Be proficient with high performance scientific computing
  • Effectively wrangle data
  • Perform data visualization
  • Design experiments

The SM in Health Data Science is designed to be a terminal professional degree, giving students essential skills for the job market. At the same time, it provides a strong foundation for students interested in continuing in a PhD in Biostatistics or other quantitative or computational science with an emphasis in data science.

health data science masters usa

5. Rutgers University – New Brunswick, New Jersey

Master’s of Business and Science (MBS) in Analytics-Health Informatics Pathway


Average Graduate Tuition: $17,232/yr in-state and $29.304/year out-of-state
Faculty to Student Ratio: 15:1
Score: 8
The Professional Science Master’s Program at Rutgers University features a fully online Master of Business and Science focused on analytics. Students with a background in health or the healthcare industry can complete the health informatics pathway which includes coursework in:

  • business intelligence visual analytics
  • project management
  • Python
  • the interpretation of data

Most of the program can be completed online but students do need to come to campus for a one-week intensive each year. Worried about finding a job after graduation? Over 96% of Rutgers graduates are employed within six months of graduation.

4. University of Alabama – Birmingham, Alabama

Master of Science in Health Informatics-Data Analytics

Average Graduate Tuition: $8,100/yr in-state and $18,540/year out-of-state
Faculty to Student Ratio: 19:1
Score: 8
The University of Alabama Birmingham School of Health Professionals features a master’s in data analytics. It’s designed for busy professionals who need an affordable degree option. The unique blended format includes online courses and two-three day residencies. Courses cover areas such as:

  • healthcare requirements analysis
  • databases and data modeling
  • strategic planning and contracting
  • principles of health informatics

Most students can complete their degree in just 24 months.

3. University of North Carolina at Charlotte – Charlotte, North Carolina

Health Informatics and Analytics (HIAN) Program


Average Graduate Tuition: $4,337/yr in-state and $17,771/year out-of-state
Faculty to Student Ratio: 19:1
Score: 8
The University of North Carolina at Charlotte features a top master’s in health informatics and analytics that has been recently revamped. Courses are focused on:

  • data science
  • system architecture
  • health analytics

The addition of a capstone course to the internship requirement provides students with practical application opportunities. Full-time students can complete the program is about four semesters while part-time students finish in eight.

2. Northeastern University – Boston, Massachusetts

MS in Health Data Analytics


Average Graduate Tuition: $24,027/yr
Faculty to Student Ratio: 14:1
Program Tracks: Personal Health Informatics or Population Health
Score:9
The top master’s in health data analytics at Northeastern University is a flexible campus-based program that takes two to three years to complete. The competency based curriculum focuses on relevant areas such as:

  • data aggregation methods
  • data mining algorithms
  • visualization techniques
  • predictive computational modeling

The program is designed for students with a background in health and medicine and skills in statistics and computer science. Graduates are prepared to become Certified Health Data Analysts.

1. University of Louisville – Louisville, Kentucky

MS in Health Data Analytics


Average Graduate Tuition: $12,684/yr in-state and $26,454/year out-of-state
Faculty to Student Ratio: 15:1
Score: 9
The Department of Health Management and System Sciences at the University of Louisville features a flexible master’s in health data analytics that trains students in the practical application of data analytics to public health and medicine. The program is taught by world-class faculty with industry experience. The curriculum focuses on four main areas including:

  • public health foundations
  • principles of data warehouse construction
  • advanced analytics
  • applications

Students can complete their degree, including coursework, capstone, and internship/practicum in just two years.

msc health data analytics uk

COURSE OVERVIEW

If you are working in a healthcare role that involves analysing health data, this MSc Health Data Science degree, could accelerate you into one of the fastest growing areas in the UK.

This course is designed to develop the essential skills and knowledge you’ll need as a Health Data Scientist. Our degree offers strong emphasis on practical and analytical skills that you can apply in the workplace and could make you more employable. It is available as a one year full time or three years part time course.

Healthcare already has an established strong relationship with Information and Communication Technologies (ICT), and is continuously expanding the knowledge forefront as new methods of acquiring data concerning the health of human beings are developed. On this course you’ll learn how processing this data to extract valuable information about a population (epidemiological applications) has the potential to improve quality of life on a large scale.

WHY STUDY HEALTH DATA SCIENCE AT SWANSEA UNIVERSITY?

  • 1st in the UK for Research Environment, 2nd in the UK for Research Quality – Research Framework (Research Excellence Framework 2014)
  • Postgraduate students have access to facilities in the £100 million Institute of Life Science building
  • What Uni? Student Choice Award 2017 Winner – Postgraduate
  • Degree is available as either one year full time or part-time over three years
  • Strong links with the NHS and organisations within the Life Science Sector
  • Strong collaborative links with colleagues from the Centre for Health Services Research of the University of Western Australia, a group of leading experts in the analysis of linked health data
  • Hands on experiential learning from the professionals behind the Secure Anonymised Information Linkage (SAIL) Databank, a UK-exemplar project for the large scale mining of healthcare data within a secure environment

YOUR HEALTH DATA SCIENCE EXPERIENCE

Your degree experience will be enhanced by access to state of the art facilities based within our Centres for Excellence for Administrative Data and Health Research of Swansea University, awarded by the Economic and Social Research Council (ESRC) and Medical Research Centre (MRC). This course is delivered in collaboration with high profile staff from the Centre for Health Services Research of the University of Western Australia.

HEALTH DATA SCIENCE EMPLOYMENT OPPORTUNITIES

We have carefully designed the course to provide you with an increased knowledge and understanding of Health Data Science, and the skills and aptitude you need to apply your learning to professional practice.

As such, this Master’s degree will give you the in-depth knowledge of the field to potentially enhance your prospects for career progression.

MSc Health Data Analytics and Machine Learning

Overview

Our MSc in Health Data Analytics and Machine Learning* is a one-year full-time course aimed at building a solid and common background in analysing health data.

Your main objective is to develop skills in using appropriate cutting edge quantitative methods to fully exploit complex and high dimensional data.

The course is delivered in collaboration with the Data Science Institute, with teaching from both the School and Institute undertaken by international experts with strong methodological background and expertise in the application of these approaches to large-scale medical and clinical data.

Each module and the six-month research project includes project-based work. Projects are based on real data and will address real scientific questions from research staff within School of Public Health, Data Science Institute and industrial partners.

Study programme

The programme is a full-time 12 month taught Master’s course, which runs from October-September.

The course is divided between six core taught modules and one six-month research project.

In term one, you share your first two modules with MSc Epidemiology and Master of Public Health students, ensuring a common foundation in epidemiology. The third core module is specific to this course.

You will also set and agree a research project focus in your first term.

In term two, you turn your focus to statistical methods in the three remaining core modules, as well as continuing in-depth planning for your research project.

Your third term is predominantly made up of the research project.

Careers

Graduates of this course will have acquired the strong methodological background needed to perform in-depth analysis of medical and epidemiological high throughput datasets.

You will graduate prepared to pursue further study at doctoral level, become an expert analyst in industry, and join large data companies.

* taught sessions with Data Science Institute at South Kensington

Structure

Modules shown are for the current academic year, and are subject to change depending on your year of entry.

You take all of the core modules below.

  • Clinical Data Management
  • Computational Epidemiology
  • Introduction to Statistical Thinking and Data Analysis
  • Machine Learning
  • Principles and Methods in Epidemiology
  • Research project
  • Translational Data Sciences
Cheapest Data Science Masters In The World – College Learners

Teaching and assessment

Teaching

  • Case studies
  • Formal presentations
  • Group work exercises
  • Lectures
  • Seminars and practical coding activities

Assessment

  • Individual and group coursework
  • Oral presentations
  • Research project report
  • Written examinations

Medical Data Science

Medical Data Science M.Sc.

Program Description

Digital technologies are revolutionizing many areas – including health care. Thanks to digitalization, therapies and other care services can now be developed that are individualized and patient-centered. Medical Data Science – that is, the collection, processing, and analysis of data – aims to link care and research. Doing this helps us better understand diseases, select therapeutic approaches that are more personalized while also allowing us to predict their therapies’ effects better.

The course of study is designed to accommodate further education students or those employed part-time. It allows participants to learn about medical data science while continuing their regular professional activities at the same time.

The educational concept of the degree program follows three objectives:

  1. Medical data and medical data software aspects will be put in a systemic, socio-technical, and regulatory context concerning both care and research. Instructors will teach students these aspects using a spiral approach, which will guide them through the various modules while offering a high degree of practical relevance.
  2. The program offers students an integrative, collaborative approach at the interface of medicine and computer science that will also teach them the necessary interdisciplinary professional competencies. Small interdisciplinary learning groups make it possible to learn from, with, and about each other and allow participants insight into different professional and cultural backgrounds.
  3. A blended learning approach allows students to design their part-time studies in a flexible and largely individualized manner by being able to combine face-to-face instruction on campus with periods of online learning that involve both contact hours and self-study components.
Master Data Science In 1 Month – College Learners

Degree Content

The standard period of study is four semesters. In the first and third semesters, the course content is divided into four modules. The second semester comprises three modules. In addition, an internship or project work is completed this semester. The semester modules are taught via online seminars and, at regular intervals, as block courses on campus in Aachen. RWTH’s modern learning platform also provides students with interactive content. The fourth semester is reserved for writing the Master’s thesis.

Based on participants’ prior knowledge, they will begin with one of the two starting tracks, “Medical Aspects” or “Computer Science Aspects.” These two tracks each consist of two modules. This approach ensures that all applicants will have the necessary foundational knowledge in medicine and computer science to have a common baseline of understanding going forward. In the third semester, all participants can choose between the two specialization tracks, “Data Integration” or “Data Analytics” with two modules each.

Prerequisites

A prerequisite for admission to studies is a first university degree and at least one year of relevant professional experience. The required professional qualification is formulated in the examination regulations. The board is in charge of determining whether or not prerequisites have been fulfilled.

Career Prospects

Successful graduates of the “Medical Data Science” Master’s degree program will have acquired skills and competencies that enable them to gather medical data from a variety of sources and also clean and merge those data sets. They will have both fundamental medical and technical knowledge to prepare for medical decisions regarding diagnostics and therapy. This will enable them to improve patient care and drive pioneering medical research.

They will be able to structure and manage complex information systems that achieve high-quality information processing results. As medical data science experts, they will provide the foundation for innovative, data-driven diagnostics and therapy – data integration – or take advantage of, or develop, methods to analyze large amounts of data and to advance machine learning – data analysis – in a medical context. Keeping in mind the ethical, legal, and social aspects of health informatics while also reflecting on their personal role and professional development, they will be able to offer extensive expertise in the area of project and change management in interprofessional contexts.

Their ability to design digitized processes in health care offers successful graduates of the “Medical Data Science” master’s degree program a wide range of opportunities for personal and professional development in an interdisciplinary working environment.

Course Summary

The MSc in Health Data Analytics and Machine Learning course aimed at building a solid and common background in analysing health data. Your main objective is to develop skills in using appropriate cutting edge quantitative methods to fully exploit complex and high dimensional data. The course is delivered in collaboration with the Data Science Institute, with teaching from both the School and Institute undertaken by international experts with strong methodological background and expertise in the application of these approaches to large-scale medical and clinical data.

The programme features extensive project-based learning using real data sets and addressing real scientific questions through module-specific projects work, and individual research projects. This Master’s is integrated in the research priorities of the School of Public Health, the Data Science Institute, the MRC Centre for Environment and Health, the UK Dementia Research Institute, and the pan-London Health Data Research UK initiative, through: the contribution to teaching of key staff members (lectures, seminars, journal clubs) and the definition of research projects stemming from data available and yet under-exploited in each institute.

As such, not only the programme will equip students with cutting-edge statistical and machine learning techniques that are required to explore emerging ‘Big’ health data, but will also provide extensive experience in their application in a real-life setting in Environmental, Molecular, Cancer, and Computational epidemiology as well as in Population and Health sciences. Graduates of this course will have acquired the strong methodological background needed to perform in-depth analysis of medical and epidemiological high throughput datasets. You will graduate prepared to pursue further study at doctoral level, become an expert analyst in industry, and join large data companies.

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