Presencial en Reino Unido
También en Online
MSc: 2250 hours / 180 CAT (90 ECTS)
PGDip: 1500 hours / 120 CAT (60 ECTS)
June 2026
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.
What clinical laboratory equipment will you use?
You will only need a computer for this course. During your training ,you will also work with Python, one of the main programming languages.
The route to your future
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.
Characteristics of the MSc Medical Laboratory Science
Audio visual study material
- You will have access to many hours of audio visual materials, which are essential teaching materials. Thus, you can study wherever and whenever you want.
Practical activities
- Approximately twice a week you will carry out practical activities that will be reviewed and evaluated by your specialized teachers.
Complementary material
- Class summaries, articles to stay up-to-date... You will have everything you need to keep on learning.
Master class
- You will learn from well-known experts in the medical sector thanks to our master classes, which you can watch as many times as you want.
MSc / PGDip final project
- At the end of the course you will conduct a research project on a topic of your interest. One of our teachers will supervise your project.
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!
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!
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.
Enrolment and preparation
- As soon as you enrol, you will have access to the virtual platform. We will also start your employability plan. Let is get going!
Videos and online classes
- Videos, PDF summaries and live classes from your teachers.
Exercises and questionnaires
- You will regularly test your knowledge to move steadily towards your goals.
MSc final project
- You will carry out a bibliographic research project on a topic of your interest.
Optional internships
- Let is get to work! From 60 to 300 hours of optional internships available in a wide range of companies.
As your journey progresses, you will discover different modules which will help you, step by step, to reach your final goal.
Module 1. The Background
1. The fourth industrial revolution
2. A brief history of the interaction between medicine and artificial intelligence
3. What can we use AI algorithms for in the clinical setting?
4. Learning systems: A mapping of the AI environment
5. Health data: sources and characteristics
6. Data Protection: GDPR
7. Research and clinical trials
8. Ethical implications
9. 5Ps Medicine
10. Value-based decision
11. European/national/regional/regional strategy
12. Expected impact of AI in the coming years
13. Resource management success cases
14. Health care success cases
Exam
Module 2. The technique
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
Module 3. Applications of AI in healthcare
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
Module 4. Implementation of AI projects in Healthcare
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
Major Project
Conviértete en el perfil híbrido que más demanda tiene en el sector salud. Este máster online te prepara para aplicar IA en contextos clínicos reales y liderar proyectos de salud digital, tanto si vienes del ámbito tecnológico como sanitario. Aprenderás a integrar datos, automatizar procesos y colaborar en equipos que desarrollan soluciones innovadoras para diagnóstico, tratamiento y gestión clínica...
PRóXIMA CONVOCATORIA EL 9 DE JUNIO Y LA SIGUIENTE EL 13 DE OCTUBRE.
CEMP
El Máster en Big Data, Análisis de Datos e Inteligencia Artificial (MBDA) está diseñado para ti. Con este programa, adquirirás las competencias necesarias para dirigir proyectos de Big Data de principio a fin, implantando una auténtica cultura Data Driven en tu empresa.
Aprenderás a tomar decisiones con menos incertidumbre y mayor impacto, gracias al dominio de herramientas como Power BI, fundamentos sólidos en arquitectura de datos, y el uso avanzado de inteligencia artificial, machine learning, cloud computing y ciberseguridad...
Gigantes como Google, Microsoft, Facebook, Amazon y Oracle están realizando una intensa inversión en las nuevas tecnologías inteligentes, creando un cambio de paradigma que no solo está transformando el presente a pasos agigantados, sino que, además, dibuja un panorama en que la Inteligencia Artificial cambiará de manera radical la forma de trabajar, de hacer negocios, y la vida de los usuarios, durante los próximos años...
Según el informe “Empleos y Sectores Emergentes 2024” de la patronal tecnológica DigitalES, los puestos de trabajo relacionados con la inteligencia artificial han experimentado un crecimiento del 454% de media en los últimos cinco años. Cifras que refrenda el World Economic Forum, al indicar que espera que la IA cree 2...
La demanda de profesionales de Big Data no ha dejado de crecer. En España existe actualmente una escasez de talento en este sector y las empresas tienen dificultad en encontrar candidatos adecuados para esta área. Esto se traduce en el aumento en los salarios y el pago de las personas que tienen el conjunto de habilidades requeridas...
El máster en Inteligencia Artificial de la Escuela de Inteligencia Artificial y Big Data IMF x Indra tiene como objetivo responder a la demanda de profesionales que deseen especializarse en este ámbito. Se pretende que el alumno obtenga un punto de vista técnico y metodológico, acompañado de una incorporación práctica de las técnicas y métodos aplicados a la realidad social y empresarial...
