
Master’s Degree in Data Analytics and Artificial Intelligence in Health Sciences (DAIHS)
Milan, Italy
DURATION
2 Years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
14 Feb 2025
EARLIEST START DATE
Sep 2025
TUITION FEES
EUR 20,156 / per year
STUDY FORMAT
On-Campus
Introduction
The 2-year Master’s Degree in Data Analytics and Artificial Intelligence in Health Sciences (DAIHS) is an exciting new learning opportunity. It is designed to train a professional figure with an understanding of the healthcare sector and the theoretical and practical knowledge required to implement AI and Machine Learning methods.
Entirely taught in English, the course stems from the extensive medical, biological, and healthcare experience in medicine provided by Humanitas University and its joint Hospital networks, and the extensive experience in AI, data science, and data analytics from Bocconi University.
The partnership between Humanitas University and Bocconi University will guarantee training in medical biology, statistics, mathematics, and computer science in the pursuit of improved care and quality of life for patients.
Scholarships and Funding
1 merit and income-based scholarship is available
Curriculum
The study plan has been structured to merge disciplinary fields from data science with disciplinary fields from the medical-biological field.
This will allow advanced training in statistics, computer programming, machine learning, and artificial intelligence, to be combined with knowledge of biology, genetics, ethics, and regulation within the healthcare sector.
The study plan for DAIHS aims to develop a cultural and professional profile that can directly contribute to the improvement of both patients’ lives and healthcare organizations.
To reach this objective, the study plan has been structured to merge scientific disciplinary fields from the LM Data Science degree class, with scientific disciplinary fields from the medical-biological field. This will allow us to combine deep training in advanced programming, statistics, Machine Learning, and Artificial Intelligence with solid knowledge of biology, genetics, ethics, and specific regulation within the healthcare sector.
The course is structured over two years and will be held entirely in English. International lecturers and experts with strong professional experience abroad are part of the faculty of the DAIHS course.
Students will also have the opportunity to learn in international experiences as part of the development of the dissertation.
The 1st year is mainly focused on providing the necessary knowledge in advanced programming, statistics, Machine Learning, and Artificial Intelligence, and due to these characteristics, it is mainly based at Bocconi University. The 2nd year takes place at Humanitas University to immerse students into the reality of a large teaching hospital, working on biological and clinical data.
Study Plan
The first year is mainly focused on providing the necessary knowledge in advanced statistics, programming, machine learning, and artificial intelligence, and it is mainly based at Bocconi University. The final part of the first year, and the whole second year, complements training mainly within Humanitas University, through an immersive, hands-on learning experience that includes the delivery of compulsory integrated teaching, elective exams, seminars, hands-on experiences, and independent research.
Students will also have the opportunity to learn during international experiences as part of the development of their thesis and internship.
1st Year
- Advanced Statistics for Health Sciences
- Advanced Computer Programming
- Artificial Intelligence – Module 1
- Privacy, Ethics, and Regulations in the Application of AI – Seminar
- Machine Learning
- Artificial Intelligence – Module 2
- Data Systems in Healthcare
- 1 elective course out of:
- Causal Inference
- Natural Language Processing
- Dynamic Modelling for Complex Systems
- Causal Inference
- Natural Language Processing
- Dynamic Modelling for Complex Systems
- Biology and Genetics
- Data Science for Clinics
- Clinical Epidemiology
2nd Year
- Next Generation Sequencing and Bioinformatics
- Applications of Artificial Intelligence in Health Sciences
- 1 elective course out of:
- AI and Visualisation-Navigation Techniques in Surgery and Endoscopy
- AI Applied to Imaging (radiology and human pathology)
- Clinical Decision System and AI
- AI and Visualisation-Navigation Techniques in Surgery and Endoscopy
- AI Applied to Imaging (radiology and human pathology)
- Clinical Decision System and AI
- Guidelines for Quality Assessment and Reporting in AI Publication – Seminar
- Foreign Language (1st sem)
- Internship
- Thesis
Career Opportunities
This Master’s Degree Course aims to train professional figures with an understanding of the healthcare sector and deep knowledge of the theoretical and practical knowledge required to implement AI and machine learning methods in that sector.
The Role of Data Scientist in Health Sciences
Graduates in this role will effectively extract, analyze, model, and interpret health data through the application of state-of-the-art analytical techniques derived from statistics, machine learning, and artificial intelligence, to obtain answers useful for scientific research. They will also interpret clinical-diagnostic-therapeutic pathways, understand the demands of clinicians and basic researchers, and identify software tools needed for clinical and biological data processing and analysis. Lastly, they will design and conduct scientific studies in the field of medicine and health sciences by collaborating effectively with health professionals and researchers from different disciplines.
They may be employed by a variety of employers, including research institutions, pharmaceutical and biotechnology industries, health technology companies, public bodies and government institutions, hospitals and healthcare organizations, startups in the healthcare industry, consulting and professional services, and research institutions.
Graduates of the program will be able to:
- Design and implement a complete process of statistical analysis of health data, from acquisition to extraction of the information of interest, with a special focus on methods and algorithms from Machine Learning and Artificial Intelligence
- Build predictive models from data
- Design and develop software to perform the analysis and interpret the results of health data analysis
- Represent and communicate the results from analyses
- Describe and implement procedures for the protection of data quality, privacy, and intellectual property
English Language Requirements
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