OVERVIEW

The teaching unit is about the basics of information and communication technologies (ICT) associated with Internet, cybersecurity, and machine learning in the framework of energy applications.

AIMS AND CONTENT

LEARNING OUTCOMES

The course aims to provide the student with essential knowledge on issues of telecommunications networks and signal processing / analysis in contexts related to systems for energy production, with particular attention to the field of Industry 4.0. At the end of the course, the student will know the basic principles of telecommunications networks, the main technologies / standards related to wired and wireless networks applicable in industrial environments, the architecture and Protocols of the Internet and the basic aspects related to the theme of cyber security. He will also have learned the essential concepts related to the representation of analog and digital information and data analysis using machine learning

AIMS AND LEARNING OUTCOMES

After the teaching unit, the student will have learnt the basic principles of telecommunication networks, the architectures and the protocols of Internet, and the basic aspects of cyber security. The student will also have learnt the basic concepts associated with information representation through analog and digital signals and with machine learning. The concepts learnt through the teaching unit will be framed in the context of energy applications.

PREREQUISITES

There are no specific requirements.

TEACHING METHODS

Class lectures.

Students with a certified learning disability (DSA), a disability, or other special educational needs are invited to contact the instructor at the beginning of the course to discuss teaching and examination arrangements that, while respecting the learning objectives of the course, take individual learning needs into account and provide appropriate accommodations.
Please also note that requests for exam accommodations or exemptions must be submitted using the form available at https://modulionline.unige.it/richiesta-adattamenti#no-back, to the course teacher, the DIME contact person (federico.scarpa@unige.it), and the relevant office (inclusione.studenti@info.unige.it) at least seven working days before the examination, in accordance with the guidelines available at https://unige.it/disabilita-dsa/richiesta-servizi

SYLLABUS/CONTENT

• Basic principles of telecommunication networks
• Internet architecture and protocols
• Basic aspects of cyber security
• Basic principles of information representation through analog and digital signals
• Basic aspects of signal analysis through machine learning
• Case studies of machine learning applications in the energy field
• Introductory concepts of deep learning

RECOMMENDED READING/BIBLIOGRAPHY

• Slides used in class and made available on AulaWeb
• Hastie T., Tibshirani R., and Friedman J., The elements of statistical learning, Springer, 2008
• Bishop C., Pattern recognition and machine learning, Springer, 2006
• Bishop C., Bishop H., Deep learning, Springer, 2024
• Carlson A. B., Crilly P., Communication systems, McGraw-Hill, 2009
• Goodfellow I., Bengio Y., and Courville A., Deep learning, MIT Press, 2016
• Kurose J. F. and Ross K. W., Computer networking: a top-down approach, 7th Edition, McGraw-Hill, 2017
• Stallings W., Data and computer communications, 10th Edition, Prentice Hall, 2013
• Stallings W., Wireless communication networks and systems, Global Edition, Prentice Hall, 2016
• Tanenbaum A. S. and Wetherall D. J., Computer networks, 5th Edition, Prentice Hall, 2010

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/11438/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Oral examination on the topics included in the syllabus of the teaching unit.

ASSESSMENT METHODS

Within the oral examination, the student's knowledge of the teaching unit topics and his/her capability to discuss how to apply and use the studied ICT methodologies and technologies in the energy field shall be evaluated.

FURTHER INFORMATION

Ask the professor for other information not included in the teaching schedule.