Lab of Computer Skills (Political Science)

Course Formative Objectives

The course provides the basis for understanding the working principles of modern digital technologies and their implications on our daily life at individual and organisational level. The objectives of the course can be divided into two main categories related to theoretical and practical aspects, as described below.

  • Theoretical aspects: Understanding the concept of “Computational Thinking” and its application in social and economic sciences; understanding algorithm principles and fundamentals of programming languages as well as concepts of data structure, information and coding; understanding the combination of hardware and software components that makes up modern digital devices especially those used in business. Understanding the main features of modern communication networks, the architecture of the web, and the cloud computing. Understanding the concept of mobile computing, mobile applications and IoT; understanding social network phenomenon; understanding the basic concept of database and the potential of BigData analysis as a tool for decision support; Understanding information security key concepts; being aware of the perils arising from malicious software and from the exposure of corporate and/or personal sensitive information; understanding the concept of machine learning and digital currencies.
  • Practical aspects: introduction to programming, useful for developing an alternative problem solving approach and for understanding fundamental programming principles to be adopted in finance and statistics applications.


Main topics

Theoretical part:
– Course introduction; what is computational thinking; binary notation; definition of algorithm
– Algorithms, data structures and programming languages
– HW/SW components and architectures
– Networks fundamentals and application protocols
– Network resources, cloud computing and Web search
– Mobile computing, mobile devices, mobile applications and IoT
– Social network and graph concepts
– Data Base, BigData
– Information Security and Privacy
– Machine learning
– Digital Currencies
Practical part
– Introduction to Python
– Data type and data structure
– Variables and constants
– Conditional (if) statements and Loops
– Functions
– Recursive functions
– Search algorithms
– Numerical Algorithms

Course materials

Students can find class materials on the e-learning platform (slides, lecture notes, and the text book reference).

Assessment Method

The theoretical competences are assessed via oral or written format (on the basis on the number of students). A practical test in the lab is used for assessing the technical skills.