OVERVIEW

The course will focus mainly on the basic elements of computer science, with theoretical topics exemplified with appropriate practical applications. Furthermore, basic mathematical elements necessary for both the understanding of computer science and the quantitative approach to the other teachings of the course of study will be included.

AIMS AND CONTENT

LEARNING OUTCOMES

IT skills (with particular reference to skills relating to digital health, health IT and management IT) are among the qualifying objectives of the degree class and are essential contents. In particular, the teaching will be dedicated to providing basic knowledge to be able to deal with topics relating to the management of traceability flows of medicines and medical devices, pharmacovigilance flows, pharmaceutical supervision and device-vigilance, database consultation and interaction with the telematic systems of the SSR and the SSN, management of the warehouse and galenic laboratory in compliance with the NBF, telemedicine, CUP, electronic prescriptions.

AIMS AND LEARNING OUTCOMES

-Understand all the rather disparate topics that currently constitute the discipline of information technology.

-Be able to use most of the tools that the evolution of computer science makes available to us with full knowledge of the facts.

-Enable students to design small portions of databases

-Enable students to use the main mathematical tools necessary in the other courses of the degree course

Open Badge: ability to learn to learn

TEACHING METHODS

Fromtal lessons and exercises

Working students and students with DSA, disability or other special educational needs certification are advised to contact the teacher at the beginning of the course to agree on teaching and exam methods which, in compliance with the teaching objectives, take into account individual ways of learning

SYLLABUS/CONTENT

Introduction:

• Algorithms
• Abstraction
• Data storage

Bits and binary system

• Main memory
• Mass memory
• Representation of information
• Numbers and their representation
• Compression and error handling
• Data processing:

Computer architecture

• Machine language
• Execution of programs
• Logical-arithmetic instructions
• Communication with other devices
• Data abstraction:

Basic concepts

• Implementation of data structures
• Classes and objects
• Image Processing:

Definition of images

• Image manipulation
• Noise
• Compression
• Filtering

Database structures:

• Layered approach to database construction
• Relational model
• Database integrity management

Practise:

• Use of text editors
• Use of spreadsheets
• Use of image management tools
• Use of databases
• Design of simple relational databases

Mathematics section

• Equations, Inequalities, Systems of equations
• Functions
• Derivatives
• Integral

RECOMMENDED READING/BIBLIOGRAPHY

J. Glenn Brookshear, D. Brylow “Informatica: Una panoramica generale” 13°Ed. Pearson Milano-Torino 2020.

TEACHERS AND EXAM BOARD

Exam Board

MAURO GIACOMINI (President)

NORBERT MAGGI

LESSONS

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

Written and Oral.

ASSESSMENT METHODS

Written and oral examination of the topics discussed

Exam schedule