Cybersystems – Multimedia and Digital Arts

Multimedia and Digital Arts

The Multimedia and Digital Arts track (closely connected with the Internet and Security one, which you can find here) revolves around multimedia data production and processing in a multidisciplinary fashion.


It focuses on the application of multimedia data production and processing to the booming field of digital arts.

How does the study plan work

A list of the courses available in the Multimedia and Digital Arts curriculum for the 2022-2023 academic year is reported below.


The mandatory courses are Internet and Multimedia (composed of Internet and Computer Vision) and Digital and Interactive Multimedia.

The other courses can be freely chosen subject to some ground rules: at least 5 courses from the ICT subjects and 3 courses from the related subjects must be chosen. Furthermore a soft skill course must be selected and students must pass the B2 English exam.


It is further advised to choose about 30 ECTS credits per semester to keep your workload balanced.

Our core subjects:

Our related subjects:

Mandatory Courses

The Internet and Multimedia course is mandatory.

It is made of 2 parts: Internet and Computer Vision.

Furthermore the Digital and Interactive Multimedia course must also be taken.

Internet (mod. A of Internet and Multimedia)

The course aims at providing basic knowledge of modern telecommunication architectures, as well as fundamental mathematical tools for the modelling, design and analysis of telecommunications networks and services. 

The course will also give you some practical experience with network protocols and devices, thanks to a series of lab experiences that will introduce you to the art of router and socket programming.

Ancillary to all this knowledge, the course will help you develop some basic management skills that shall belong to the baggage of each engineer.

Some of the topics that will be considered by the course are data traffic sources, multimedia streams and content, packet switched networks: basics of data networks, ISO/OSI and TCP/IP protocol stacks, congestion control and scheduling algorithms and the application layer.

Computer Vision (mod. B of Internet and Multimedia)

The computer vision course presents the principles and techniques for image processing, understanding and analysis.

The course will show how to extract relevant information from visual data that can be used in challenging real world applications like autonomus driving or smart manifacturing.

It presents the mathematical, programming, and technical issues of these tasks and will include a relevant hands-on laboratory part where students will also develop C++ applications based on the OpenCV library.

Digital and Interactive Multimedia

Course details will be available soon

ICT Subjects

Select 5 courses from the following list

3D Augmented Reality

The course offers a guided tour of 3D computer vision, 3D graphics and machine learning tools to develop virtual and augmented reality applications.


After a description of imaging systems, the course reviews how to build a 3D model starting from 2D pictures and/or depth sensors, also by means of machine learning techniques, and finally the process of rendering real or virtual 3D models to standard images and 3D/AR devices.


Students will experience computer vision, deep learning and augmented reality techniques during lab sessions.


A beginners' tutorial on Unity will be provided as well.

Digital Forensics

This course presents machine learning and signal processing technologies that can be used handling digital evidences in investigations.


The aim is to provide students with a set of analysis strategies for hard disk, network streams, image and video data (including authentication and fake detection), data from social networks.


These techniques are reviewed and discussed both theoretically and via some case studies.


The course entails the intervention of legal specialists that describe the procedural implications of the technical analysis and the juridical consequences on expert decisions.

Digital Signal Processing

The course exploits basic signal analysis knowledge that the student is assumed to have acquired from previous studies to explore advanced concepts in the field of digital signal processing.


The course will review Z-transform, linear time-invariant systems, FIR/IIR filters, to investigate the design and usage of digital filters, interpolation/decimation of digital signals, frequency analysis of digital signals. Practical application examples, useful in many areas of information engineering, will be provided.

Game Theory

Game theory is the science of analyzing multi-objective multi-agent problems (i.e., "games").


This involves the games we usually play for fun in our everyday life, but in a more serious context is applied to resource competition, distributed management, efficient allocation over multi-user systems and/or communication networks.


This course teaches all the basic concepts, as well as some advanced ones, of game theory. Also, it applies them to scenarios of interest for ICT.

Information Theory

Course details will be available soon

Internet of Things

This course provides knowledge of the concepts of the "IoT" and "Smart cities," describing their scientific and market trends, as well as the application of these paradigms in practical ICT context.


The students will learn about some key platforms and standards (ZigBee, 6LoWPAN, WiFi, Bluetooth Low Energy, SigFox, Lo-Ra), and will review their applications for home automation, industrial applications, autonomous driving, urban monitoring, privacy and security.

Machine Learning

Intelligent systems capable of automated reasoning are emerging as the most promising application of ICT.


The aim of this course is to provide fundamentals and basic principles of the machine learning problem as well as to introduce the most common techniques for regression and classification.


Both supervised and unsupervised learning will be covered, with a brief outlook into more advanced topics such as Support Vector Machines, neural networks and deep learning.


The course will be complemented by hands-on experience with Python programming.

Multimedia Coding

The goal of the course is to provide the principles and tools needed to analyze and develop techniques for compression of multimedia data.


Both lossless and lossy coding techniques will be considered.


Methodologies for the evaluation of coding gain and rate distortion will also be discussed. Finally, applications to present coding standards will be presented, such as data (ZIP), audio (MP3), pictures (JPEG), and video (MPEG) compression, as well as their implication to multimedia communications.

Network Analysis and Simulation

The course gives instruments for theoretical analysis and computer simulation of distributed systems.


During the classes, simulation software and mathematical tools will be reviewed, and applied to scientific examples taken from the literature.


The expected outcome for the student is to master different characterizations of network systems and their performance metrics, result interpretation, and design of optimization criteria.

Network Science

The course describes networking phenomena over many scenarios.


Although communication networks and the Internet are primary references, similar representations can be used for social networks, ecological systems, and epidemic diseases.


The course describes network generation models, and then community structures are reviewed, also outlining the applications to online social communities, brain networks, and biological systems.

Neural Networks and Deep Learning

The course covers the theory and practice of modern artificial neural networks, highlighting their relevance both for machine learning applications and for modeling human cognition and brain function.


Topics include single-neuron modeling and principles of neural encoding; supervised, unsupervised and reinforcement learning; feed-forward and recurrent networks; energy-based models; large-scale brain organization.


Theoretical discussion of various types of network architectures and learning algorithms is complemented by hands-on practices in the computer lab (PyTorch framework).

Video Communication and User Experience

This course is about theory and application of video compression for communications. The course covers the theoretical foundations of signal compression, describes the most common and most recent video compression standards (H.264, HEVC, VVC, MPEG), and focuses on the quality of experience of video streaming services. Laboratories are a relevant part of the course. The students will be guided to the implementation of a simplified but functional video encoder. 

Related Subjects

Select 3 courses from the following list

Computer Engineering for Music and Multimedia

Course details will be available soon

Digital Storytelling

Course details will be available soon

History of Animation

Course details will be available soon

Human Computer Interaction

The course targets the principles of user-centered design, cognitive ergonomics, user experience, and usability to investigate how the human experience of interacting with automated computing machines can be made simple, pleasant, and overall satisfactory.

Case studies from websites, apps, smart city applications will be presented and paradigm and design criteria will be reviewed and discussed.

Also, the program will touch accessibility and universal design of interfaces as well as social computing and ergonomics.

Natural Language Processing

The course has three main goals: (i) learning of the techniques and methodologies at the basis of NLP; (ii) development of hard skills for the design of end-to-end NLP systems; (iii) development of soft skills needed for team-working and problem solving.

Reinforcement Learning

Course details will be available soon

Soft Skills

Select 1 course from the following list.

Public Speaking Lab

The lab aims to help students improve their oral communication through the study and practice of the elements contributing to successful communication.


The focus is on raising the students' awareness on the importance of verbal and non verbal language in interactions to make communication more effective.


The students will learn the meanings of body language and paralanguage (voice intonation, volume, etc), how they are used in different types of interactions (one-to-one, one-to-many, computer-mediated, etc.), and will have to apply them in a number of assigned tasks.


The lab requires the students' active participation in all class activities, aimed at applying the communication strategies learned.

Project Management

This course will provide the foundations of the project management.


Traditional (such as the Project Management Institute approach) as well as more advanced techniques - such as the Agile Methodology - will be reviewed.


Special focus will be put on the methodologies more suited for the ICT environment.

Public values in media and ICT

More details will be available soon.

Elective credits

Select one course (6 ECTS) among all the courses of this Master’s (free choice). In addition, you have to select two courses (up to 15 ECTS) from this Master’s or any other one of the University of Padua, submitted to the condition of being relevant for the ICT scientific area.


These are mandatory activities

English language B2

Students must certify that they have a proficiency level "English B2" according to the CEFR scheme. To this end, students can:
  • Submit a certificate issued by a recognized external certification agency;
  • Take an internal test at the University of Padova Language Centre (CLA) to verify that they can interact with a degree of fluency and spontaneity that makes regular interaction with native speakers quite possible without strain for either party.
Recognized certifications

Final project

Students are asked to carry out a substantial individual project in their final year.


The project can be carried out either at the University of Padova (30 ECTS combining a 21 ECTS Final Project and a 9 ECTS Report), or in an external institution, such as an Industry or a Research Center, either national or international (30 ECTS combining a 21 ECTS Final Project and a 9 ECTS Internship).


It is also possible to do the internship in an external institution, and the final project at the University, though we suggest to carry out the whole work in a single place.

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