12 monthsProgramme duration
30,750 GBPTuition Fee/year
SepStarting Month
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The development and use of machine learning (ML) and artificial intelligence (AI) have revolutionised areas such as computer vision, speech recognition and language processing.
On this course you will learn how to apply ML and AI techniques to real scientific problems. This will help you build vital skills, enhancing your employability in a rapidly expanding area.
Graduates of this course will learn how to:
Find out what our graduates say about the course on our Physics Blog.
You will have the opportunity to develop your own research project on a topic of your choice. Previous projects have looked at:
On this course you will learn how to apply ML and AI techniques to real scientific problems. This will help you build vital skills, enhancing your employability in a rapidly expanding area.
Graduates of this course will learn how to:
- identify and use relevant computational tools and programming techniques
- apply statistical and physical principles to break down algorithms, and explain how they work
- design strategies for applying machine learning to the analysis of scientific data sets.
Find out what our graduates say about the course on our Physics Blog.
You will have the opportunity to develop your own research project on a topic of your choice. Previous projects have looked at:
- Deep Learning for drug discovery
- Machine Learning for sustainable solvent selection
- Quantum reinforcement learning
- Supervised machine learning on a quantum computer
- Deep Learning network for fatigue monitoring of wind turbine blades
- Shaking all over – vibration cancellation at the atomic level
- Using machine learning to automatically segment the placenta from pregnancy MRI scans
- Machine learning assisted high-throughput computational screening of metal organic frameworks for biogas upgrading
- Simulating the Universe
- Detecting dark matter substructure in galaxies
- Personalised modelling of cerebral blood flow from multi-modal features for early detection of dementia
- Machine Learning natural product biosynthesis
- Advanced natural language processing in Fintech
Programme overview
Main Subject
Data Science and Artificial Intelligence
Degree
MSc
Study Level
Masters
Study Mode
On Campus
The development and use of machine learning (ML) and artificial intelligence (AI) have revolutionised areas such as computer vision, speech recognition and language processing.
On this course you will learn how to apply ML and AI techniques to real scientific problems. This will help you build vital skills, enhancing your employability in a rapidly expanding area.
Graduates of this course will learn how to:
Find out what our graduates say about the course on our Physics Blog.
You will have the opportunity to develop your own research project on a topic of your choice. Previous projects have looked at:
On this course you will learn how to apply ML and AI techniques to real scientific problems. This will help you build vital skills, enhancing your employability in a rapidly expanding area.
Graduates of this course will learn how to:
- identify and use relevant computational tools and programming techniques
- apply statistical and physical principles to break down algorithms, and explain how they work
- design strategies for applying machine learning to the analysis of scientific data sets.
Find out what our graduates say about the course on our Physics Blog.
You will have the opportunity to develop your own research project on a topic of your choice. Previous projects have looked at:
- Deep Learning for drug discovery
- Machine Learning for sustainable solvent selection
- Quantum reinforcement learning
- Supervised machine learning on a quantum computer
- Deep Learning network for fatigue monitoring of wind turbine blades
- Shaking all over – vibration cancellation at the atomic level
- Using machine learning to automatically segment the placenta from pregnancy MRI scans
- Machine learning assisted high-throughput computational screening of metal organic frameworks for biogas upgrading
- Simulating the Universe
- Detecting dark matter substructure in galaxies
- Personalised modelling of cerebral blood flow from multi-modal features for early detection of dementia
- Machine Learning natural product biosynthesis
- Advanced natural language processing in Fintech
Admission Requirements
6.5+
90+
71+
3+
2.1 (or international equivalent) in one of the following areas: physics, mathematics, computer science, chemistry, engineering. A high 2.2, above 56%, (or international equivalent) may be considered if the applicant has relevant work experience or another supporting factor.
12 Months
Sep
Tuition fees
Domestic
12,750 GBP
International
30,750 GBP
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