Fundamentals of Computer Science
A.Y. 2020/2021
Learning objectives
The course aims at providing the students with the basics related to the computer and information science. In particular: i) formal definition of information; ii) semiotic models of communication; iii) database modelling; iv) network architecture (client - server); v) internet and world wide web: protocols and standard; vi) markup languages (html). Starting from the basics, the course presents advanced topics such as information retrieval and graph theory to analyze the digital communication and advertising. Finally, AI is introduced specifying its scope and applications so to framing the current debate on the related topics.
Expected learning outcomes
Formal definition of information
Communication Model (Shannon Weaver)
ER model and relational model
Relational algebra and SQL
Client server architecture
TCP-IP and HTTP protocols
Basics of HTML
Adserving workflow
Basics of web analytics
Basics of Information Retrieval
Graph Theory
Search engine
Social Network Analysis
AI and Machine Learning basics
Communication Model (Shannon Weaver)
ER model and relational model
Relational algebra and SQL
Client server architecture
TCP-IP and HTTP protocols
Basics of HTML
Adserving workflow
Basics of web analytics
Basics of Information Retrieval
Graph Theory
Search engine
Social Network Analysis
AI and Machine Learning basics
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
First semester
The course will be held in distance mode, mainly in synchronous way, through Teams.
Course syllabus
The course aims at providing the students with the basics related to the computer and information science. In particular:
i) formal definition of information;
ii) models of communication;
iii) database modelling;
iv) network architecture (client - server);
v) internet and world wide web: protocols and standard;
vi) markup languages (HTML / XML).
Starting from the basics, the course presents advanced topics such as
a) information retrieval
b) graph theory
c) social network analysis
d) privacy: technical issues
e) the digital communication and advertising
f) basics of AI and ML.
i) formal definition of information;
ii) models of communication;
iii) database modelling;
iv) network architecture (client - server);
v) internet and world wide web: protocols and standard;
vi) markup languages (HTML / XML).
Starting from the basics, the course presents advanced topics such as
a) information retrieval
b) graph theory
c) social network analysis
d) privacy: technical issues
e) the digital communication and advertising
f) basics of AI and ML.
Prerequisites for admission
No prior knowledge is required.
Teaching methods
The lessons will be held on the Microsoft Teams platform and can be followed synchronously based on the timetable.
Teaching Resources
S. Castano, A. Ferrara, S. Montanelli, Informazione, conoscenza e Web per le scienze umanistiche, Pearson, Milano 2009
Lecture Notes
http://www.cs.cornell.edu/home/kleinber/networks-book/ chap1, 2, 13, 14
Lecture Notes
http://www.cs.cornell.edu/home/kleinber/networks-book/ chap1, 2, 13, 14
Assessment methods and Criteria
The final exam will be oral.
During the course, non mandatory exercises will be held and can influence the final evaluation.
During the course, non mandatory exercises will be held and can influence the final evaluation.
Unita' didattica A
INF/01 - INFORMATICS - University credits: 3
Lessons: 20 hours
Unita' didattica B
INF/01 - INFORMATICS - University credits: 3
Lessons: 20 hours