Control Systems Engineering
Italy, Padua
| Study location | Italy, Padua |
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| Type | Master's degree, full-time |
| Nominal duration | 2 years (120 ECTS) |
| Study language | English |
| Awards | (Master of Science in Control Systems Engineering) |
| Course code | IN2546/000ZZ/2021 |
| Accreditation | to be approved |
| Tuition fee | €2,739 per year For further information please visit: www.unipd.it/en/tuition-fees |
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| Application fee | €30 one-time This fee is non-refundable. |
| Deposit | €204 one-time In order to accept your place at the University of Padua, the payment of the admission fee is required. This fee is non-refundable. |
| Entry qualification | Bachelor diploma (or equivalent)
The entry qualification documents are accepted in the following languages: English / Italian. You can often get a suitable transcript from your school. If this is not the case, you will need official translations along with verified copies of the original. You must take the original entry qualification documents with you when you finally go to the university. If you are admitted to the degree course, you will have to submit other documents including original and translated/legalised copies of your previous qualifications, etc. No legalised documents are required at application stage. |
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| Language requirements | English B2 Level (CEFR) or equivalent Please check out this link for the full list of accepted certificates, minimum scores and exemptions |
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| More information |
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Overview
The Master’s degree aims at training engineers with the ability to model, analyze and control the behavior of a wide array of robotics, industrial, financial, biological and information systems and networks. Particular emphasis is placed on learning and design methods that employ the best available data analysis, artificial intelligence and optimization methods.
Programme structure
The programme offers four paths that focus on different aspects of contemporary control system engineering, as well as the opportunity to create your own:
1 – Robotics: models and control techniques for single or groups of interacting cyber-systems;
2 – Machine Learning: artificial intelligence and statistical methods for automatic learning dynamical models and the optimal ways to control them;
3 – Industrial Automation: methods and technologies used in state-of-the-art industrial automation systems;
4 – Complex Systems: advanced modeling and control techniques for engineering and research in complex physical, biological and information processing systems.
Career opportunities
Graduates work as professionals in industries with a highly technological profile, or in environments that require skills in modeling, analyzing and governing complex and networked systems, such as consulting companies, research centers and public administration. The acquired skills are designed to be portable and easily adaptable to the quickly evolving job market.
Central European Time
Central European Time