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Master's Degree in Data Science

Data Science for Intelligent Systems

Data Science for Intelligent Systems

Contact Person: Prof. Giovanni Acampora - Dep. of Physics Ettore Pancini, Monte Sant'Angelo Campus.

Intelligent systems can be viewed as an organized aggregation of theories and methodologies from computer science, physics and engineering, whose main goal is the deployment of computer systems characterized by enhanced features such as sensing, proactive reasoning, learning, and action planning.
Autonomous vehicles, medical diagnostic systems based on image processing, cognitive robotics, and natural language processing represent only few examples of intelligent systems supporting people's daily activities and improving their lifestyles.
The specialization "Intelligent Systems" of the Master’s Degree in Data Science of the University of Naples Federico II is aimed at training the future generation of researchers and practitioners able to deal with the fundamental mechanisms of human reasoning and use this knowledge to design and develop intelligent systems in different application domains.

Moreover, the trainees in the specialization "Intelligent Systems" will be capable of implementing their ideas on classical computational architectures and quantum computing frameworks, such as the IBM QX processors family.

Remember, that the free choice exams can be selected amongst the whole course catalogue of the Polytechnic and Fundamental Sciences School, as long as they are coherent with the selected formative path.

Course CFU Notes
Curricular course n. I  12 Specific to the selected curriculum
Curricular course n. II 6 Specific to the selected curriculum
1-st Free Choice Course 6 Only constraint: the course must be coherent with the formative trajectory of the student (read below)
2-nd Free Choice Course 6 Only constraint: the course must be coherent with the formative trajectory of the student (read below)
Internship-Stage or Project 8 Second semester 
Other activities 6 Any Time
Thesis and Final Exam 16 Second Semester
Total CFU - First Year   60  

 

Recommended choices

Activity CFU Course Department S.S.D.
Curricular course I 12 Computational Intelligence and Machine Learning for Physics Dept. of Physics INF/01
Curricular course II 6 Computational Neurosciences Dept. of Physics BIO-09
Free Course** 6      
Free Course** 6      
**Suggested Free Course (2 courses to be selected 6 Astroinformatics Dept. of Physics FIS/05
6 Quantum Computing Systems Dept. of Physics FIS/03
6 Artificial Intelligence and Quantum Computing Dept. of Physics INF/01
6 Machine Learning for Physics Dept. of Physics INF/01