Find your postgraduate
Optional internship
MSc: 2250 hours
PGDip: 1500 hours
Optional internship
Online
Dual degree
MSc: 180 CAT (90 ECTS)
PGDip: 120 CAT (60 ECTS)
Employability
plan
MSc: £9,588
PGDip: £7,188
Enrolment Fee: £560
This MSc / PGDip Artificial Intelligence for Healthcare will provide a broad introduction to AI’s enormous potential and will prepare you to lead multidisciplinary teams that develop Artificial Intelligence projects in healthcare organisations and related industries.
With this online MSc / PGDip you will gain a broad overview of the technical, regulatory, economic and ethical aspects needed to develop AI projects in the healthcare sector. You will learn basic concepts of programming and data processing, as well as the Artificial Intelligence models that can be applied to diagnosing and monitoring different pathologies. By the end of the course, you will have an understanding of the tools needed to implement AI projects and methodologies across the healthcare sector.
You will have access to many hours of audio visual materials, which are the essential teaching materials. Thus, you can study wherever and whenever you want.
During your journey, you will carry out around two weekly practical activities, which will be reviewed and evaluated by your specialist teachers.
Class summaries, articles to stay up-to-date… You will have everything you need to move forward on your journey.
You will learn from renowned experts in the sector thanks to our master classes, which you can watch as many times as you want.
At the end of your route, you will carry out a research project directed by one of our teachers on a topic of your interest.
Our highly specialized professors and instructors will unlock the learning potential
in all our students and open the doors
to employability with a MSc / PGDip
Artificial Intelligence for Healthcare.
BSc and MSc in Biology, doctor in Microbiology from the University of Galway Ireland.
Her work has been specifically dedicated to the design, development and validation of rapid nucleic acid based diagnostics for the detection and identification of microbial contaminants. She has built a strong scientific background with >10 years of practical research experience working in the academic sector. Author and coauthor of about 10 peer-reviewed international journals.
MEDICAL DOCTOR CHEMICAL PATHOLOGIST
Dr. Yohann Missiak, a Toulouse-based Medical Doctor, excels in Chemical Pathology and AI Machine Learning, leading healthcare data analysis at INOVIE (Groupe). Proficient in R, Python, and Javascript, his career spans clinical biochemistry, biostatistics, and AI research, reflecting his commitment to advancing medical knowledge with a Doctor of Medicine degree from Université Paul Sabatier Toulouse III.
PHD IN CHEMICAL SCIENCES
Daniel holds a PhD in Chemical Sciences. Daniel is a specialist in innovation management and holds master's degrees in ISO 9000 and EFQM quality systems, R&D&I management systems, and R&D&I project management and management systems and technological surveillance, among others. He is currently the CEO of Qubiotech Health Intelligence S.L. and a professor at the University School of Labour Relations and Human Resources at the University of A Coruña.
PHD IN PHYSICS
Jesús holds a PhD in Physics and holds an MSC in Particle Physics and its technological and medical applications. Jesús has dedicated a large part of his career to research, both in foundations and at the University of Santiago de Compostela. In addition, he has been the technical director of a company in the AI sector applied to healthcare.
BSC IN PHYSICAL SCIENCES
Juan holds a BSc in Physical Science. He works as a consultant in artificial intelligence applied to health and specialised in analysis and data mining, Juan Francisco has extensive national and international experience leading projects on artificial intelligence applied to health. He is also an expert in team management and electronic health record projects. He is currently completing a master's degree in advanced and applied artificial intelligence.
BIOMEDICAL ENGINEER
Andrea holds a BSc in Biomedical Engineering from the Polytechnic University of Madrid. She currently works as an R&D engineer at Qubiotech Health Intelligence, developing software for automatic medical image analysis.
PHD IN PHYSICS
Juan Pablo holds a PhD in Physics and extensive experience in scientific data processing in C++ and Python environments, software development for medical image analysis and R&D project management. Juan Pablo currently works at Qubiotech as head of the R&D&I team, directing development projects and actively participating in the technical implementation of the specifications.
PHD IN BIOCATALYSIS
Marta holds a PhD in Biocatalysis and a BSc in Agricultural Engineering. Marta is passionate about biostatistics and AI. In addition, Marta holds two MSc degrees in Biomedical Informatics and Big Data and has worked in clinical and biomedical data analytics. Furthermore, she has a wide range of experience both as a researcher and a teacher.
From the first to the last stage of your training, we will always be by your side to help you make the most of every step.
As soon as you enrol, you will have access to the virtual platform. We will also start your employability plan. Let's get going!
Videos, PDF summaries and live classes from your teachers.
You will regularly test your knowledge to move steadily towards your goals.
You will carry out a bibliographic research project on a topic of your interest.
Let’s get to work! From 60 to 300 hours of optional internships available in a wide range of companies.
You have arrived at your destination! You now have your own CEMP qualification, University of Chichester university accreditation*, and EQAC accreditation*. It's time for new challenges... and new adventures!
*see accreditation conditions.
I want my CEMP certificate! I want my CEMP degree!As your journey progresses, you will discover different modules which will help you, step by step, to reach your final goal.
Exam
1. Rule-based expert systems. The predecessors of AI
2. Machine Learning: regression, classification and clustering models
3. Neural networks and deep learning
4. The learning paradigm. Feature selection and model optimisation
5. What is Python? Introduction. Python and data science. Installation and working environment
6. Getting started in Python (Theory) Data types, variables, operators, loops and other structures
7. Getting started in Python.(Practical) Data types, variables, operators, loops and other structures
8. Object orientation: classes and instances, attributes and methods. Working with libraries
9. Fundamental Python libraries for working with data: Numpy and Pandas
10. Introduction to AI in Python. Libraries and levels of abstraction
11. Data analysis in Python: Spicy, Matplotlib, Seaborn, statsmodels
12. Data structuring: data sets for training, validation and testing. Data augmentation
13. Machine Learning in Python: Scikit-learn and practical examples
14. Neural Networks in Pyhton: Pytorch, Tensorflow and Keras
Exam
1. Types of data in health
2. Hospital Information Systems (HIS) and Electronic Health Records (EHR)
3. Image Management Systems (PACS and DICOM)
4. Data interoperability in healthcare. The FHIR standard
5. Text mining and Natural Language Processing (NLP)
6. Medical image analysis. U-Nets and GANs
7. Robotic Process Automation
8. Artificial Intelligence and Cloud Computing
9. Decision Support Systems: Diagnosis and Treatment
10. AI in Drug Discovery and personalised treatments
11. Management improvements
12. Patient interaction and telemedicine
Exam
1. Framework evaluation Outcome-Action-Pair (OAP)
2. Life cycle of an IA project
3. Design and development
4. Validation
5. Monitoring and maintenance
6. Relevant actors IA Health
7. Bias, interpretability and fairness
8. Privacy and security
9. Regulatory environment
10. Implementing an AI strategy
11. Corporate intrapreneurship and cultural change
12. Project management
13. Public and private financing tools for innovative projects
Exam
Why enrol in our Postgraduate Certificate in Artificial Intelligence for Healthcare? Because in addition to having prestigious professors and a curriculum aimed at preventing student drop-out, we guide our students towards achieving their professional goals.
Learn more about the employability plan you'll benefit from the moment you sign up.
This MSc programme opens doors to diverse careers in healthcare and technology. Graduates can excel in healthcare data analysis, medical imaging, clinical decision support, and more. Prepare for exciting AI-driven healthcare careers!
Our MSc Applications of Artificial Intelligence for Healthcare has a total duration of 2250 hours . This is equivalent to 180 UK credits, the workload typically associated with an academic year. You can also choose our PGDip, which has no Major Project included and has a duration of 1500 hours (120 UK CAT).
You will only need a computer for this course. During your training ,you will also work with Python, one of the main programming languages.
At CEMP, we offer online training programs that are fully adapted to the needs of each person, with tailored payment instalments available worldwide , to make sure each student is able to complete all stages of their postgraduate course successfully. To find out more about fees and payment plans, contact us through the online form and one of our friendly and experienced team will be in touch.