LEARNING OUTCOMES

The aim of the course is to introduce the student to the main concepts related to the management of large quantities of data on computers (database) and their use in applications developed to enable input, handling and management of such data. The course will provide knowledge about the main databases in use (relational and associative model) and on the related technical and practical features. The knowledge of object oriented programming in Python will be given as an instrument to interact with database and develop applications that can persist data beyond the standard predefined data structures in Python. During the course the student will leanr how to implement simple databases and interact with them through Python scripts. As for capabilities, the student will learn how to choose the best model for a specific task, and choose the best implementation of data structures to interact with a specific database.

AIMS AND LEARNING OUTCOMES

The aim of the course for the Python programming language part, is to introduce the student to the following topics:

• object-oriented design and programming;
• using pre-defined and user-defined data structures efficiently;
• using libraries for file manipulation;
• creazione e utilizzo di eccezioni per la gestione degli errori;
• introduction to the libraries numpy, matplotlib and pandas to analyze and present data.

Regarding databases, the aim of the course is to introduce the student to the following topics:

• introduction to databases
• relational databases
• SQL language to create and query relational databases
• progettazione di basi di dati con diagrammi entità-relazione

The main learning outcome will be the ability to combine programming skills in Python with database engineering skills in order to build applications that, starting from row data, can process them, insert them into a database to enable efficient querying and presentation of  data.

PREREQUISITES

The course requires basic knowledge of the Python programming language (types, expressions, conditional statements, iteration statements, function definition, predefined data structures). Even if the course starts with a quick review of these concepts, a good grasp on them is preferrable to follow the course.

TEACHING METHODS

The course is taught with standard classes and labs. Most classes will be hands-on, where the main concepts will be explained through examples and extensive interaction will take place. Some classe will be mainly based on slides. During labs students will have a chance to solve some exercises with teacher guidance. Classe and labs might be delivered online.

SYLLABUS/CONTENT

The course focuses on the following topics:

• Variables, expressions, string types
• Control structures
• Lists: features and performances
• Tuples and ranges: features and performances
• Sets: features and performances
• Dictionaries: features and performances
• Console IO and file handling
• Regular expressions, modules and packages
• datatime module, mathematical and numerical modules
• Collections and heapq module
• Class definition and implementation
• Inheritance and polymorfism
• Iterators and generators
• Errors and exceptions
• Structured testing
• Introduction to databases
• Relational model
• Using SQL as Data Definition Language
• Design of databases
• Entity-relationship diagrams
• Logic design
• Using SQL as Data Manipulation Language
• Normalization

RECOMMENDED READING/BIBLIOGRAPHY

Tony Gaddis - Introduzione a Python - Pearson (Informatica)

Paolo Atzeni, Stefano Ceri, Piero Fraternali - Basi di Dati - McGraw Hill