Recently, big data, analytics, artificial intelligence, and the Internet of Things have posed new problems and opened new perspectives in the field of software systems development. The teaching aims to illustrate these changes and to provide approaches/techniques/methods to support the development of systems based on these innovative technologies (shortly smart systems).
The students will be encouraged to complement the presented material by independently deepening some topics, in the spirit of lifelong learning.
Learning new problems posed by the development of smart systems, and learning some approaches/techinques/tools to support their development.
At the end of the course, students will be able to:
* UNDERSTAND the specific problems posed by the development of smart systems;
* CAPTURE and SPECIFY the requirements of smart systems;
* UNDERSTAND, EVALUATE and PRESENT to a group of peers state-of-the-art approaches for supporting the development of smart systems.
Basic knowledge of software engineering.
Lessons, and lab activities (capture and specification of the requirements of a smart system).
Introduction to the problems posed by the development of systems based on (big) data, analytics, artificial intelligence, and the Internet of Things (shortly smart systems).
A method based on goals and UML for the capture and specification of the requirements of smart systems.
MLOps and other DevOps specialisations for the development of systems fueled by data and machine learning.
State-of-the-art methods, approaches and tools for designing smart systems.
Material provided by the teacher
Ricevimento: Appointment to be required by email
GIANNA REGGIO (President)
According to the calendar approved by the Degree Program Board: https://corsi.unige.it/en/corsi/11964/studenti-orario
The exam consists of three parts:
Guidelines for students with certified Specific Learning Disorders, disabilities, or other special educational needs are available at https://corsi.unige.it/en/corsi/11964/studenti-disabilita-dsa
The quality of the project's results will enable the evaluation of students' capabilities to apply the selected method to a real-world case.
The discussion of the project results will enable the assessment of the contributions of each student.
The oral presentation will enable the evaluation of the students' communication and self-learning capabilities.
For further information, please refer to the course’s AulaWeb module or contact the instructor.
