Health Data Science MSc 12 months Postgraduate Program By UCL |Top Universities
Program Duration

12 monthsProgram duration

Tuitionfee

36,500 GBPTuition Fee/year

Main Subject Area

Medicine Related StudiesMain Subject Area

Program overview

Main Subject

Medicine Related Studies

Degree

MSc

Study Level

Masters

Study Mode

On Campus

This programme covers computational and statistical methods as applied to problems in data-intensive medical research. As part of this programme, you will gain an understanding of techniques that are transforming medical research and creating exciting new commercial opportunities.

You will learn how to link and analyse large complex datasets. You will also design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The programme draws on a range of areas, including epidemiology, computer science, statistics and other fields, such as genetics.

Students undertake modules to the value of 180 credits.

The programme consists of five compulsory modules (75 credits), three optional modules (45 credits), and a dissertation (60 credits).

A Postgraduate Diploma, five compulsory modules (75 credits), three optional modules (45 credits), full-time one year, part-time two years or flexible study up to five years, is offered.

A Postgraduate Certificate, two compulsory modules (30 credits), two optional modules (30 credits), full-time one year, part-time two years or flexible study up to five years, is offered.

Upon successful completion of 180 credits, you will be awarded a MSc in Health Data Science. Upon successful completion of 120 credits, you will be awarded a PG Dip in Health Data Science. Upon successful completion of 60 credits, you will be awarded a PG Cert in Health Data Science.

Program overview

Main Subject

Medicine Related Studies

Degree

MSc

Study Level

Masters

Study Mode

On Campus

This programme covers computational and statistical methods as applied to problems in data-intensive medical research. As part of this programme, you will gain an understanding of techniques that are transforming medical research and creating exciting new commercial opportunities.

You will learn how to link and analyse large complex datasets. You will also design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The programme draws on a range of areas, including epidemiology, computer science, statistics and other fields, such as genetics.

Students undertake modules to the value of 180 credits.

The programme consists of five compulsory modules (75 credits), three optional modules (45 credits), and a dissertation (60 credits).

A Postgraduate Diploma, five compulsory modules (75 credits), three optional modules (45 credits), full-time one year, part-time two years or flexible study up to five years, is offered.

A Postgraduate Certificate, two compulsory modules (30 credits), two optional modules (30 credits), full-time one year, part-time two years or flexible study up to five years, is offered.

Upon successful completion of 180 credits, you will be awarded a MSc in Health Data Science. Upon successful completion of 120 credits, you will be awarded a PG Dip in Health Data Science. Upon successful completion of 60 credits, you will be awarded a PG Cert in Health Data Science.

Admission Requirements

185+
3.3+
7+
69+
100+
A minimum of an upper second-class Bachelor's degree, or equivalent, in a clinical or a scientific discipline with a significant computational or mathematical element.

1 Year
Sep

Tuition fees

Domestic
16,000 GBP
International
36,500 GBP

Scholarships

Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.

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