University of Parma

What you'll study

This programme blends core data science subjects with management-oriented modules and applied projects. Teaching typically covers statistical foundations, machine learning, data engineering and scalable computing alongside courses in business analytics, innovation management and data-driven strategy.

• Core technical modules: probability and inferential statistics, supervised and unsupervised machine learning, deep learning fundamentals, time series analysis and natural language processing.
• Data engineering and infrastructure: database systems, data modelling, ETL, cloud computing and big data platforms (distributed computing frameworks and architectures).
• Management and applied analytics: business intelligence and visualisation, managerial decision making, operations research, project management and entrepreneurship for data-driven products.
• Ethics, law and governance: data protection, algorithmic fairness, privacy-preserving analytics and regulatory aspects relevant to data-driven services.
• Practical components: laboratory sessions, team projects with real datasets, internships with industry or public organisations, and an individual master’s thesis or capstone project focused on an applied research or development problem.

Entry requirements

Applicants are normally expected to hold a recognised undergraduate degree in a quantitative discipline such as computer science, engineering, mathematics, statistics, economics or a related field. Candidates with degrees in other disciplines but with demonstrable quantitative skills and programming experience may also be considered.

• Academic transcript showing completion of a bachelor-level qualification (or equivalent) with appropriate coursework in mathematics, statistics or computer science.
• Evidence of practical programming experience (for example, coursework, projects or a portfolio demonstrating proficiency in languages such as Python, R, or SQL).
• Motivation statement or personal statement explaining interest in data science management and relevant experience.
• Possible interview or assessment task for shortlisted applicants; some applicants may be asked to provide references.
• Proof of language proficiency where required (Italian and/or English) depending on the language of instruction for specific modules.

Career prospects

Graduates are prepared for roles that bridge technical data work and strategic decision-making. Typical career paths include:

• Data Scientist or Machine Learning Engineer, developing predictive models and analytic solutions.
• Data Analyst or Business Intelligence Specialist, turning data into actionable insights for business units.
• Data Engineer, designing and maintaining data pipelines and infrastructure.
• Analytics Consultant or Product Manager, combining domain knowledge with data-driven strategy to shape services and products.
• Roles in specialised sectors such as agri-food analytics, manufacturing analytics, healthcare informatics, finance and public sector data management.
• Research and academic pathways, including doctoral study in data science, artificial intelligence or management science.

Why study at University of Parma

The University of Parma offers an interdisciplinary environment with strengths in computational sciences, economics and applied research, enabling a curriculum that links advanced analytics to real organisational contexts. The university maintains collaborations with regional industry—particularly in the agri‑food and manufacturing sectors—which provides opportunities for applied projects and internships.

Students benefit from hands‑on laboratories, access to research groups working on machine learning and data-driven innovation, and opportunities to engage in international collaborations. The programme emphasises transferable skills in communication, project management and ethical practice to prepare graduates for leadership roles where data and management intersect.