About
The Course aims to train experts in highly relevant and rapidly growing fields within the Computer Science and Engineering sector, such as the processing and extraction of information from large datasets (Big Data and Data Science), and tools and technologies for Advanced Robotics, both for industrial applications and for civil and service contexts. These fields are home to some of the most sought-after professional profiles in today's job market. The programs of the various subjects have recently been updated and expanded with modern content on artificial intelligence, also with regard to software infrastructures based on the use of Large Language Models.
Some of the specific objects of the Course are:
- Design and management of complex IT systems and services, including in the field of big data;
- Design of data-driven and data-intensive systems, also based on modern artificial intelligence models;
- Design and application of technologies and services for virtualization and cloud computing;
- Management of key aspects of cybersecurity and data security;
- Analysis of large datasets and design of predictive models in various socio-economic, political, and industrial application domains;
- Design and application of visualization techniques for the presentation and interactive analysis of complex data;
- Design and application of deep learning and reinforcement learning techniques for computer vision;
- Design and development of autonomous robotic systems, such as autonomous vehicles (drones and other autonomous vehicles);
- Design and development of advanced driver assistance systems;
- Design and development of applications for the management and control of energy systems;
- Modeling, analysis, optimization, and simulation of complex dynamic systems;
- Design of motion control systems for industrial and mobile robots;
- Design and development of systems for industrial automation and home automation;
- Support for the design of biomedical systems and automatic medical devices.
Some courses in the program are taught in English. Furthermore, regardless of the language of instruction, each course provides teaching materials in English.
Curricula - study tracks
The Course offers two alternative study tracks (curricula). Select you favorite curriculum to view details.
| First year (2025-2026) | ||
|---|---|---|
| Subject | CFU | Language |
| Machine Learning and Data Analysis | 9 | en |
| Internet and Web Programming | 6 | it |
| Intelligent and Secure Networks | 9 | it |
| Information and Estimation Theory | 9 | en |
| Computational Models and Advanced Algorithms | 9 | it |
| Software Engineering and AI-enabled Systems | 9 | it |
| Second Year (2026-2027) | ||
|---|---|---|
| Subject | CFU | Language |
| Models and Algorithms for Data Visualization | 9 | en |
| Signal Processing and Optimization for Big Data | 9 | it |
| Artificial Intelligence in Cloud Computing | 9 | it |
| One of the following | ||
| Data Intensive Applications and Big Data | 6 | en |
| Data Security and Blockchain | 6 | it |
| Deep Learning | 6 | en |
| One of the following | ||
| Data Science for Health Systems | 6 | it |
| Deep Learning | 6 | en |
| Free choice | 15 | |
| English qualification B2 (*) | 3 | |
| Thesis | 12 | |
(*) The English language qualification must be achieved at the CLA (University Language Center).
| First Year (2025-2026) | ||
|---|---|---|
| Subject | CFU | Language |
| Machine Learning and Data Analysis | 9 | en |
| Embedded Electronic Systems | 9 | it |
| One of the following | ||
| Digital Signal Processing | 9 | en |
| Intelligent and Secure Networks | 9 | it |
| Machine to Machine Networks | 9 | it |
| Information and Estimation Theory | 9 | en |
| Industrial Robotics | 6 | it |
| One of the following | ||
| Computational Models and Advanced Algorithms | 9 | it |
| Software Engineering and AI-enabled Systems | 9 | it |
| Second Year (2026-2027) | ||
|---|---|---|
| Subject | CFU | Language |
| Deep Learning and Robot Perception | 9 | en |
| Autonomous Robotics | 9 | it |
| Nonlinear and Robust Control | 9 | en |
| One of the following | ||
| Data Intensive Applications and Big Data | 6 | en |
| Data Security and Blockchain | 6 | it |
| Internet and Web Programming | 6 | it |
| One of the following | ||
| Signal Processing and Optimization for Big Data | 9 | it |
| Artificial Intelligence in Cloud Computing | 9 | it |
| Free choice | 12 | |
| English qualification B2 (*) | 3 | |
| Thesis | 12 | |
(*) The English language qualification must be achieved at the CLA (University Language Center).
Access to the Course
Enrollment
Enrollments in the Course with the regular procedure are possible until the end of February. After this date, and until the end of April, late enrollment is still possible. For more details and to complete the enrollment process, please contact the student office of the Department of Engineering. Also, consult the university enrollment page for further information, including details on tax and fee reductions.
Access requirements
The access to the Master's degree course in Computer Engineering and Robotics requires the possession of an Italian Bachelor's degree, or an Italian degree obtained according to the previous regulations before D.M. 509/99, or another recognized foreign qualification of at least three years. Access also requires meeting the curricular requirements (see point a) and having an adequate personal preparation (see point b) regarding the methods and general content in the basic scientific disciplines and in the engineering subjects of the LM-32 degree class
a) curricular requirements - The possession of at least 85 ECTS credits (CFUs) acquired in the following scientific-disciplinary areas: (i) basic subjects of the L-8 degree class; (ii) core subjects of the L-8 degree class, with particular reference to the fields of Computer Engineering, Electronics Engineering, and Telecommunications Engineering; (iii) core subjects of the L-31 degree class (Informatics/Computer Science). Only CFUs acquired through specific exams in university courses will be counted, and those obtained through certifications of professional knowledge and skills are excluded. In the case of a student with a foreign qualification recognized as equivalent, or in the case of holders of a degree obtained under the previous regulations before D.M. 509/99, the curricular requirements will be evaluated by a dedicated commission based on the certification of the educational path followed to obtain the degree. A student who does not meet the curricular requirements may be admitted to the Master's degree course in Computer Engineering and Robotics upon completing the necessary CFUs through a specific educational path agreed upon with the degree program.
Note: The curricular requirements are automatically satisfied by those who hold a Bachelor's degree in the L-8 or L-31 degree class.
b) personal preparation - A weighted average grade of at least 21/30, obtained in at least 50 CFUs in the scientific-disciplinary sectors mentioned in the previous point. For candidates who do not meet the established threshold, the degree program will arrange a test to assess their personal preparation. In the case of a student with a foreign qualification recognized as equivalent, or in the case of holders of a degree obtained under the previous regulations before D.M. 509/99, personal preparation will be evaluated by the commission referred to in point a) based on the student's curriculum and the certification of the grades achieved.
c) If criterion b) is not met, the student must pass an assessment test to evaluate the adequacy of their personal preparation. This evaluation test will be held before the start of the academic activities, on a date determined by the degree program, possibly agreed upon with the student interested in enrollment. The test may be written, with multiple-choice questions, oral, or a combination of both. The tests will cover the content of typical courses from the Bachelor's degree in the L-8 class and, in particular, the scientific-disciplinary sectors referred to in point a) for which the student's curriculum shows greater criticality, both in terms of CFUs and associated grades. The oral test may also include assessing the ability to solve elementary open-ended problems.
d) The Degree Program Council may arrange remedial educational activities aimed at meeting the access requirements.
e) In particular cases, the Degree Program Council may provide, for those who meet the access requirements, pathways based on the curricular requirements fulfilled and/or the result of the personal preparation assessment. These pathways will still allow the completion of the Master's degree with 120 CFUs, without additional educational activities.
Further details on the scientific-disciplinary sectors referred to in point a) are defined in the Academic Regulations.
Resources for students
Below are some links to useful information for students of the Course (select the item to view the information).
Academic Regulation and study plan
The Academic Regulations is an official document that defines the rules of the degree course. The Regulations also include the educational offer, which is the study plan (also called Manifesto of Studies). Students interested in consulting only the study plan will find a dedicated link below (this study plan coincides with the one reported in the Curricula section of this page).
Lessons and exams
Below are the links to the calendars for lessons and exams.
Calendar of the lessons - I semester
Internships
The degree program allows second-year students to complete an internship either at a company or in a university laboratory, in order to gain valuable skills in the workplace. The Department of Engineering has agreements with over 160 companies, where students can carry out an internship or thesis activity. The list includes small, medium, and large companies, including international ones with branches abroad. Students can undertake an internship within the framework of the elective choice in their study plan. All information regarding the internship regulations, the forms to be filled out, the partner companies, and access to laboratories for internal internships is available through the links provided below.
Thesis and graduation calendars
The thesis represents an important educational activity for the student and is carried out under the supervision of a faculty advisor and any potential co-advisors. The thesis activity, which can also be conducted in a corporate setting, involves the development of a complex project and the writing of an original paper. All information regarding the thesis, the graduation application, and the graduation session calendars can be found through the links provided below.
International mobility
The student has the opportunity to complete part of their educational path abroad, including for the purpose of an internship or thesis. International mobility is mainly supported by the EU Erasmus+ program. All information is available at the following link.
Post-graduation paths and opportunities
After obtaining the degree, the student can access master's programs or PhD courses. They can also obtain certification to practice as a professional engineer through a specific state exam, or use job placement services to enter the workforce.
Other information and services
The links below contain information about the various services offered by the Department of Engineering and the University of Perugia, including libraries, laboratories, the classroom reservation system, services for disabilities and learning disabilities (DSA), A.Di.S.U. services, and transportation services.