Purposes
Artificial intelligence is radically transforming professional sectors, from healthcare to law, and from management to creative design. This transformation creates an urgent need for professionals capable of understanding the potential and limitations of AI, applying it in an ethical and responsible manner, and turning it into a competitive advantage for their organizations. The Master in Applied Artificial Intelligence for Professionals: Governance, Innovation and Responsibility has been designed to meet this need. Training professionals to operate at the intersection of technology, governance and innovation, with a particular focus on the European regulatory framework set out by the AI Act and the GDPR.
The teaching approach is practice-oriented and interdisciplinary, with a focus on no-code and low-code tools that enable participants to implement AI solutions without advanced programming skills. The mASTER combines lessons, practical workshops, real-world case studies and project work, integrating blended learning, the flipped classroom and live coding workshops, thereby complementing theoretical training with practical experience that can be immediately applied in a professional context.
The feature that makes this Master so valuable is the combination of three elements: The interdisciplinary nature of the academic fields involved (computer science, law, medicine, economics and the arts); the focus on practical application, with 60 per cent of teaching time devoted to workshops and projects; and the specific emphasis on the healthcare sector, which is one of the areas with the greatest demand for AI skills. The Master’s programme is also designed for non-technical backgrounds, making AI tangible and accessible to lawyers, doctors, managers and creative professionals.
The knowledge acquired will be interdisciplinary and applicable across multiple fields, enabling students to develop applied technological skills alongside their critical and strategic evaluation, in accordance with the principles of transparency and security.
The contribution of disciplines in the fields of computing, law, medicine, economics and the arts enables a holistic response to the needs of the labour market, bridging the communication and operational gap between technologists and corporate and institutional decision-makers.
The Master is particularly useful both for professionals working in the private sector and public administration, and for recent graduates, especially in light of recent European regulatory measures, foremost among which is the AI Act. This legislation requires effective and ongoing AI governance, understood as the ability to assess the risks posed by AI systems, ensure data protection (GDPR), manage algorithmic bias and adopt a person-centred and responsible approach – elements that are now essential for the competitiveness and legal compliance of any organization.
Target Students
Target Students
The aim of the Master in Applied Artificial Intelligence for Professionals is to train professionals capable of bridging the gaps between technology, management, law, healthcare and creativity. In particular, the course is aimed at those wishing to train as specialists in applied AI, in line with international standards and the needs of the current market. The master is specifically designed for candidates without a strictly IT background: advanced programming skills are not required, but a willingness to work with data and digital tools is essential. It is therefore ideal for lawyers, doctors, managers, economists, designers and architects who wish to lead the adoption of AI in their respective sectors.
Career Opportunities
The Master trains professionals capable of bridging the gap between artificial intelligence, management, law and healthcare, thereby narrowing the divide between technologists and decision-makers and preparing them to take on roles that act as a bridge between technological complexity and the strategic and ethical needs of organizations.
The candidates may aspire to take on the following roles and/or pursue the following careers:
- AI Project Manager: a professional capable of managing complex AI projects, coordinating technical teams and business stakeholders, and ensuring that deadlines, budgets and regulatory compliance requirements are met.
- AAI Specialist for Healthcare: an expert in the application of AI solutions in clinical and healthcare contexts, with specific expertise in assisted diagnostics, medical imaging, clinical data management and GDPR compliance in healthcare.
- AI Compliance & Governance Officer: a professional specialising in managing AI regulatory compliance (AI Act, GDPR), defining ethical corporate policies and assessing the risks associated with the implementation of intelligent systems.
- Business AI Analyst: an analyst capable of identifying business opportunities through AI, assessing the return on investment of AI-driven initiatives and designing solutions integrated with existing business processes. The role also incorporates creative skills, with the ability to apply AI to the fields of design, content generation and visual communication, including the management of intellectual property rights for the works generated.
Admission Requirements
To be admitted to the Master, the candidates must have attained a Bachelor’s Degree or a Master’s Degree awarded by a university in the Italian Republic or another equivalent higher education institution. Other equivalent qualifications obtained from another university, including a foreign one, are accepted provided that they are legally recognised in Italy. Applicants holding qualifications in other degree categories.
The candidates must be fluent in English (minimum B2 level), have a basic knowledge of statistics (mean, variance, t-test) and be familiar with digital productivity tools (Microsoft Office/Google Suite).
Candidates with an academic qualification obtained abroad must provide a declaration of equivalence for their qualification, issued by the relevant Italian diplomatic or consular missions in the country where the qualification was obtained.
Applicants must meet and demonstrate that they satisfy the entry requirements by the deadlines set out by the Call for applications, failing which they will not be admitted to the Master’s selection process.
Important note: No advanced programming skills are required. Python will be used at an application level and under guidance, with a focus on no-code/low-code tools and AI productivity platforms. The Master’s programme is designed for non-IT professionals who wish to acquire practical AI skills without needing to become developers.
Educational objectives
The master is designed to combine a solid theoretical foundation with immediate practical application, and has the following specific objectives:
- Operational skills in AI tools and platforms: Acquire operational skills in the use of artificial intelligence tools and platforms, understanding how they work, their fields of application and their limitations, with particular reference to machine learning technologies and generative models.
- Practical implementation skills: Develop practical skills in the design, implementation and evaluation of AI solutions in non-technical contexts (e.g. business, law, medicine, art).
- Prompt engineering and generative models: Provide training in the effective use of basic and advanced prompts to maximise the capabilities of language models and generative models.
- Integrazione nei processi e nella produttività: Insegnare l’integrazione dell’AI con strumenti di produttività (suite office, CRM, ERP) e flussi di lavoro automatizzati.
- Integration into processes and productivity: Teach how to integrate AI with productivity tools (office suites, CRM, ERP) and automated workflows. Ethical, responsible and sustainable approach: To promote an ethical, responsible and sustainable approach to the use of AI, centred on the individual and respect for fundamental rights, including an understanding of regulations, risks and cyber security.
- Communication skills: To develop communication skills to present AI results to non-technical audiences.
- Change management and soft skills: Acquire change management and soft skills to lead the adoption of AI within organisations, managing cultural transition, staff engagement and the alignment of business strategy with technological innovation.
Didactics
The Master, established pursuant to Ministerial Decree 270/2004, has a duration of 12 months, with a total commitment of 1,500 hours, (based on the standard of 25 hours per CFU credit), of which 216 hours of classroom-based teaching, divided as follows:
- Synchronous lessons in virtual classrooms and in person: to interact directly with teachers according to a scheduled timetable.
- Individual study and research activities: to independently explore and consolidate the content learned in the Master's programme.
- Exercises and mid-term assessments: to evaluate learning levels and form part of the assessment process.
- Project work: for active experimentation with the content learned during the educational programme.
Master Diploma
The candidates will attail the I Level Master upon passing all the assessments provided, earning the required 60 CFU and passing the final examination. This consists of the presentation and discussion of an individual project relating to a real-world problem within the student’s professional field, involving the development of a working prototype, a technical and ethical report, and an oral presentation before an interdisciplinary exam board.
Tuition Fee
The tuition fee for the master is € 5.500
Registration
Students wishing to register can request an appointment with the Orientation Office by calling +39 06 3400 6000.
Faculty
The Faculty is comprised of academics and professionals with proven, long-standing experience in the disciplines covered by the programme, ensuring a high standard of teaching and a constant integration of research, teaching and professional practice.
Scientific Director
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Prof. Luigi Cinque
Scientific Director
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Prof. Alfredo Milani
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Dott. Marco Raoul Marini
Scientific Board
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Prof. Luigi Cinque
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Prof. Alfredo Milani
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Dr. Marco Raoul Marini
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Prof. Marco Cascio
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Prof. Chiara Pero
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Prof. Gian Luca Foresti
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Prof. Giuseppe Placidi
PROGRAMME
IT and Medicine Module (12 CFU)
The IT and Medicine module forms the technical and applied core of the programme, providing the fundamental skills required to understand and use artificial intelligence technologies, with a specific focus on the healthcare sector. The first course, Fundamentals of Data Science and Machine Learning, covers the essential mathematical and algorithmic foundations – linear algebra, probability and statistics – and explores both discriminative AI (CNN and LSTM models; classification and prediction) and generative AI (autoencoders, GANs, diffusion models), large language models and large multimodal models (Transformer architecture, GPT models, Claude, Gemini, LLaMA, DeepSeek), pre-trained foundation models (DINO, CLIP) and data preparation for fine-tuning. The second course, dedicated to AI in medicine, explores the most innovative applications in the fields of diagnostics, medical imaging, drug discovery and patient monitoring. This approach enables the training of professionals capable of working at the intersection of technology and healthcare, one of the sectors with the greatest growth potential for AI.
Cross-disciplinary links: the technical skills acquired in this module are directly applicable to all the other modules. An understanding of generative models is fundamental to the arts module; knowledge of Large Language Models underpins the business module (automation and CRM); an awareness of algorithmic bias is a prerequisite for the legal and ethics module; and the ability to assess the reliability of models is essential for the cybersecurity module.
Legal, Social and Economic Modules (18 CFU)
The legal and social module addresses the ethical, regulatory and social implications of artificial intelligence, which are fundamental to the informed and responsible use of AI technologies. The course focuses on the European AI Act, the GDPR and data protection regulations, the ethics of responsible AI, and data governance. This module prepares professionals to navigate the complex regulatory landscape and to implement AI solutions that adhere to the principles of transparency, fairness and social responsibility.
The Business and Economics module provides the skills needed to integrate AI into business processes and maximise organizational value. The course covers integration with Office and CRM tools (Microsoft Copilot, Salesforce Einstein), no-code automation using platforms such as Zapier and Power Automate, and the optimization of business workflows. Particular attention is paid to predictive analytics for business and the definition of AI-driven KPIs and metrics to measure the impact of AI initiatives within the organization./p>
The cybersecurity module addresses the critical aspects of AI system security, an essential element for any enterprise-level implementation. The course covers adversarial attacks, data poisoning, AI network security, best practices for resilient systems and regulatory compliance. It explores the principles of privacy by design and the specific legislation on the protection of personal data in AI systems, preparing professionals to manage the risks associated with the adoption of intelligent technologies.
Cross-functional integration: the legal module links to the medical module via GDPR compliance for health data and to the artistic module via the intellectual property rights of the works generated; the business module relies on the IT module for the use of predictive models and on the cybersecurity module for risk management in business automation; the cybersecurity module requires an understanding of AI models, acquired in the IT module, in order to assess their vulnerabilities.
Art Module (6 CFU)
The Art module explores the applications of AI in the creative and design sectors, a rapidly expanding field offering significant career opportunities. The course focuses on design and digital creativity, covering image generation, generative design and AI tools for visual communication, with particular attention to copyright and intellectual property issues relating to the works generated.
Cross-disciplinary connection: a technical understanding of generative models (Diffusion Models, GANs) is acquired in the IT module; the regulatory implications of copyright and intellectual property are explored in depth in the legal module; the commercial applications of AI-powered creative tools are explored in the business module. Even for a healthcare professional, the ability to assess the reliability of AI-generated images is now a key skill in the field of diagnostic imaging (ex. radiology).
Practical Activities (12 CFU)
- Internship (300 hours in total): An applied project based on real or simulated cases, carried out in partnership with companies and under the supervision of a tutor. This includes guided laboratory work and the integration of AI solutions into the student’s professional context.
Final Project (12 CFU)
- Final Assessment (300 hours in total): An applied dissertation addressing a real-world problem within the student’s sector, involving the development of a working prototype, a technical and ethical report, and an oral presentation before an interdisciplinary panel. The final assessment represents the culmination of the ‘common thread’, in which the student demonstrates the ability to integrate diverse perspectives – technological, legal, ethical and economic – into a cohesive project.