Course options
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Qualification
MSc - Master of Science
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Location
UCL (University College London)
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Study mode
Full time
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Start date
01-SEP-25
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Duration
1 year
Course summary
The MSc Artificial Intelligence for Biomedicine and Healthcare teaches the foundations of AI and how this technology can transform biomedical research, delivery of clinical pathways and improve healthcare.
About this degree
As a student on the MSc Artificial Intelligence for Biomedicine and Healthcare, you will be introduced to the foundations, use and development of AI approaches within the biomedical, clinical-sciences and healthcare application domains.
From diagnosis, prognosis, treatment selection to drug discovery and resource allocation, Machine Learning and AI are revolutionising the way we approach healthcare. Through its ability to analyse large quantities of complex heterogenous information, AI presents opportunities to improve care and productivity in health and care settings.
Along with foundational and applied training of the next generation of leaders, researchers and engineers in building future AI-based healthcare technologies, this program aims to raise awareness on the risks associated with a society progressively more dependent on AI and provide a learning environment to debate and brainstorm on these timely and pressing concepts. More specifically the programme will encourage students to discuss the ethical benefits that arise as a side effect of the technical capabilities of AI but also ethical issues of AI such as cost to innovation, harm to physical integrity, disappearance of jobs, lack of privacy, transparency, or informed consent.
Who this course is for
This programme is aimed at students with a background in computer science or related field, looking to strengthen their knowledge and specialise in applying it to biomedicine and healthcare domain. This MSc is fitting for applicants who enjoy problem-solving or innovating and are interested in redefining what is possible in healthcare with the goal of improving patient lives through medical robotics and AI. This MSc would appeal to students who enjoy problem-solving with an interest in designing and deploying new AI solutions aimed at transforming medical care and improving patient lives.
The foundation of your career
Employability
There is an urgent need to train a new breed of multi-disciplinary post-graduate students that are capable to effectively use AI expertise in biomedicine and healthcare. From research to clinical decision support there is an increasing demand for computer scientists able to tackle with the unique obstacles that Machine Learning and AI face in healthcare.
The programme is designed to train the next generation of computer science skilled professionals broadly working in the biomedical science and healthcare sectors (both industrial and public). You will be extremely competitive in the job-market as well as acting as a feeder pathway for the Department鈥檚 AI Centres for Doctoral Training.
Application deadline
31 July 2024
Modules
Tuition fees
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- Angola
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- Armenia
- Australia
- Austria
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- Costa Rica
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- Dominica
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- Ecuador
- Egypt
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- England
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- Eritrea
- Estonia
- Ethiopia
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- Finland
- France
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- Gambia
- Georgia
- Germany
- Ghana
- Greece
- Grenada
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- Guinea
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- Guyana
- Haiti
- Honduras
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- Iceland
- India
- Indonesia
- Iran
- Iraq
- Israel
- Italy
- Ivory Coast
- Jamaica
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- Jordan
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- Kiribati
- Korea DPR (North Korea)
- Kosovo
- Kuwait
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- Laos
- Latvia
- Lebanon
- Lesotho
- Liberia
- Libya
- Liechtenstein
- Lithuania
- Luxembourg
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- Maldives
- Mali
- Malta
- Marshall Islands
- Mauritania
- Mauritius
- Mexico
- Micronesia
- Moldova
- Monaco
- Mongolia
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- Morocco
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- Namibia
- Nauru
- Nepal
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- Niger
- Nigeria
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- Norway
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- Sweden
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拢 37,500per year
Tuition fees shown are for indicative purposes and may vary. Please check with the institution for most up to date details.
University information
University College London
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University League Table
9th
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Campus address
UCL (University College London), Gower Street, London, Camden, WC1E 6BT, United Kingdom
Subject rankings
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Subject ranking
5th out of 83
7th out of 117 2
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Entry standards
/ Max 214187 87%8th
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Graduate prospects
/ Max 10089.0 89%10th
2 -
Student satisfaction
/ Max 43.00 75%51st
14 -
Entry standards
/ Max 227208 92%7th
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Graduate prospects
/ Max 10093.0 93%16th
9 -
Student satisfaction
/ Max 42.88 72%97th
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