ALGORITHMS, DATA AND SECURITY
Syllabus
EN
IT
Learning Objectives
Nowadays, many organizations produce and/or analyse huge quantities of data, which is becoming a
key asset for their strategies. The main objective of this course is to introduce students to the notion of
algorithmic intelligence, by providing a basic toolkit of algorithmic and quantitative methods to analyse
and extract value from data, in particular Big data. In addition, since IT and data are everywhere and
Internet of Things devices increasingly surround us, the course introduces basic notions of
cybersecurity, cryptocurrencies and Distributed Ledger Technology.
Lectures will be based on oral presentations. Some kind of analysis will also be presented at the board,
and used for open discussions. Some part of every lecture will be dedicated to in-class discussions and
interaction between the instructor and students will be strongly encouraged. Some software tools for
Big data analysis will be used during the lessons, in particular for social network analysis and
recommendation systems.
key asset for their strategies. The main objective of this course is to introduce students to the notion of
algorithmic intelligence, by providing a basic toolkit of algorithmic and quantitative methods to analyse
and extract value from data, in particular Big data. In addition, since IT and data are everywhere and
Internet of Things devices increasingly surround us, the course introduces basic notions of
cybersecurity, cryptocurrencies and Distributed Ledger Technology.
Lectures will be based on oral presentations. Some kind of analysis will also be presented at the board,
and used for open discussions. Some part of every lecture will be dedicated to in-class discussions and
interaction between the instructor and students will be strongly encouraged. Some software tools for
Big data analysis will be used during the lessons, in particular for social network analysis and
recommendation systems.
Program
Topic 1 Fundamentals in algorithms and data organization
Topic 2 Recommender systems and recommendation algorithms
Topic 3 Social networks
Topic 4 Cybersecurity
Topic 5 Cryptocurrencies and Distributed Ledger Technology (Blockchain and Bitcoin)
Topic 2 Recommender systems and recommendation algorithms
Topic 3 Social networks
Topic 4 Cybersecurity
Topic 5 Cryptocurrencies and Distributed Ledger Technology (Blockchain and Bitcoin)
Books
Lecture notes and course material, including articles and videos, will be made available throughout the course through the course web site:
https://economia.uniroma2.it/ba/globalgovernance/corso/1282/.
https://economia.uniroma2.it/ba/globalgovernance/corso/1282/.
Bibliography
Lecture notes and course material, including articles and videos, will be made available throughout the course through the course web site:
https://economia.uniroma2.it/ba/globalgovernance/corso/1282/.
https://economia.uniroma2.it/ba/globalgovernance/corso/1282/.
Teaching methods
Lectures will be based on oral presentations. Some kind of analysis will also be presented at the board, and used for open discussions. Some part of every lecture will be dedicated to in-class discussions and interaction between the instructor and students will be strongly encouraged. A software tool for social network analysis and recommendation systems will be used to develop a case study.
Exam Rules
There will be a midterm and a final, plus a presentation using a software tool for network analysis. Midterm and final will be 85% of the final grade, the presentation will be 15% of the final grade. If you do not attend at least 15 2-hour lectures or do not complete successfully midterm and final, you will have to take an oral exam.