Università degli Studi di Napoli "Parthenope"

Teaching schedule

Academic year: 
Belonging course: 
Course of Bachelor's Degree Programme on MANAGEMENT ENGINEERING
Disciplinary sector: 
Year of study: 
Second semester
Hours of front activity: 



Course description

Knowledge and understanding:
Knowledge of the concepts and fundamental notions of IT at the basis of Industry 4.0, and of the techniques and tools to support Python programming.

Utilization of knowledge and understanding:
Ability to discriminate among the adoption of different information technologies in concrete applications in the context of Industry 4.0, evaluating potential benefits and possible threats.

Communication skills:
Ability to communicate with adequate technical competence and with appropriate language, illustrating the theoretical and technical motivations that underlie the fundamental choices.

Learning skills:
Ability to learn new techniques, technologies and tools that derive from the constant advancement of modern information technology, and to apply them to new projects.


Fundamentals of computer science.


The course will be structured as follows:
Course overview and Industry 4.0
Introduction to the Industrial Internet of Things
Communication protocols used in the IIoT environment
Platforms for interoperability in the IIoT environment
Devices to support monitoring and control in IIoT
Python programming elements
Advanced Python programming concepts
Scripting with Python for IIoT
Cloud Computing
Techniques for high reliability in the Cloud environment
Big Data fundamentals
Solutions for archiving and processing of Big Data
Fundamentals of automation in Industry 4.0
Mechanisms for the security of data exchanged, processed and archived in the industrial sector

The course aims at providing an introduction to recent technologies used in industry. Industrial Internet of Things architectures, technologies supporting industrial automation, cloud computing solutions for managing industrial IT services, platforms for processing big data produced in the context of the modern production chain, techniques for data security will be presented. monitoring and implementation of automation systems. The course will also provide an overview of the Python programming language, demonstrating its wide use for Industry 4.0 solutions.

Teaching Methods

Frontal lectures. Tutorials and exercises.


Course slide. Other material (lecture notes, scientific articles, other) made available by the lecturers.

Learning assessment

The exam consists of:
- a written test, aimed at ascertaining the understanding of the theoretical topics of the course and at verifying the level of mastery of the shown technical/practical aspects;
- an oral test, whose average duration is 20 minutes, aimed at further ascertaining knowledge of the course topics.
At the end of the oral exam, the student is awarded a maximum grade of 30/30.

The final grade will be awarded according to the following evaluation criteria:
30 cum laude: complete, in-depth and critical knowledge of the topics, excellent language skills, complete and original interpretative ability, full ability to independently apply knowledge to solve the proposed problems;
28 - 30: complete and in-depth knowledge of the topics, excellent language properties, complete and effective interpretative skills, able to independently apply knowledge to solve the proposed problems;
24 - 27: knowledge of the topics with a good degree of command, good language skills, correct and sure interpretative skills, good ability to correctly apply most of the knowledge to solve the proposed problems;
20 - 23: adequate knowledge of the topics but limited command of them, satisfactory language skills, correct interpretative ability, more than sufficient ability to independently apply the knowledge to solve the proposed problems;
18 - 19: basic knowledge of the main topics, basic knowledge of technical language, sufficient interpretative ability, sufficient ability to apply the basic knowledge acquired;
Insufficient: does not have an acceptable knowledge of the topics covered during the course.

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