About this course
Want to change direction? Switch careers? Upskill? This fast-track Masters is for you.
Taught in our London Campus IT suite, our MSc offers a fast-track to career success in this dynamic field.
A revolution is underway in the healthcare sector. Increasingly data science and artificial intelligence are automating tasks that used to take a long time to implement by hand. This degree will teach you how to optimise processes within the sector and you will learn from experts who have careers in the same. Data is one of the 21st century’s most valuable commodities. Understanding how to analyse, validate and interpret it to inform decision-making are key skills in just about every walk of life.
As a conversion degree, you do not need a science background. And the knowledge you gain will help you build a portfolio that will launch you into the field of data science, acquiring highly sought after skills that will greatly enhance your career pathway. The programme will cover topics such as, programming, statistics, machine learning, data visualisation and computer vision and the ethical and legal responsibilities of using data. This health variant will include bespoke modules covering medical imaging, how artificial intelligence can work hand-in-hand with humans in a healthcare and clinical setting and with real-world healthcare challenges.
In the third semester, you will have the opportunity to choose or design your own research project in a disciplinary area which can relate to your background or career goals.
Join the AI revolution in improving modern-day medical treatments!
Choose your modules
For a full Masters degree, you’ll study 180 credits over the duration of your course. Some programmes offer a Postgraduate Diploma (PGDip) qualification or a Postgraduate Certificate (PGCert) qualification. For a PGDip, you’ll study 120 credits, and for a PGCert, you’ll study 60 credits.
Introduction to Programming
Learn the fundamentals of Python coding so you can progress onto the rest of the course.
This module is assessed with programming coursework (80% of the final mark) and an open-book computer-based examination (20% of the final mark).
Type: Compulsory
Credits: 20 credits
Fundamentals of Data Science
An introduction to the principles of data science and data analysis. Topics include:
- Data Science Context: Datafication of society and the history of data science.
- Properties and types of data (e.g., quantitative and categorical data)
- Classification and regression, introduction to Kaggle and other sources of data
- Data Management: Data collection and techniques; Cleaning of data and processing; Data errors and artefacts; missing data
- Introductory statistical approaches to data: Basic mathematical concepts; Introduction to probabilities; Descriptive statistics (e.g., centrality measures) and characterizing distributions; Correlations; Statistical hypothesis testing
- Data analysis and visualization: Types of visualization and interpretation; Identifying outliers; Regression models
- Applications: Real-world data applications, including examples
This module is assessed by a presentation and project report.
Type: Compulsory
Credits: 20 credits
Understanding Artificial Intelligence
This module offers an introduction to the fundamental concepts in Artificial Intelligence, and their application. You will study topics such as:
- Origins of AI: What is AI? From early history to the Dartmouth conference and the present day; Intelligent agents, and performance measures
- Learning, Frameworks and Packages: Introduction to supervised learning; Regression; Classification; Clustering; Artificial Neural Networks; Convolutional Neural Networks; Keras; Tensorflow
- Implications for Society: Legalities; Ethics and professional implications; Social consequences
This module is assessed by a portfolio of work, in the form of a programmed code and a corresponding technical report.
Type: Compulsory
Credits: 20 credits
Artificial Intelligence as a Medical Device
This module explores the technical development and evaluation of AI as a medical device (AIaMD), and examines the key steps needed to successfully translate and adopt AIaMDs into healthcare systems, such as the NHS.
Type: Compulsory
Credits: 20 credits
Research and Application in Artificial Intelligence and Data Science
This module teaches you the necessary research skills to undertake project-based work in AI and data science with a scientific approach. You will also explore real-world applications of AI and data science, for example in healthcare, the environment, social responsibility, and engineering.
Assessment will be a mixture of coursework, a group presentation and a computer-based exam.
Type: Compulsory
Credits: 20 credits
Artificial Intelligence and Data Science Research Project
Plan and work independently on your own complex research-based problem. And report on the aims, methods and outcomes of your scientific investigation.
Type: Compulsory
Credits: 60 credits
Medical Imaging and Artificial Intelligence
In this module you will understand the role of medical imaging processing and analysis, and a multitude of Medical Imaging modalities. You will also understand some practical applications of ultrasound, CT, MRI, molecular imaging, and microscopy imaging. You will gain knowledge of medical imaging processing techniques.
Type: Compulsory
Credits: 20 credits
