Programming and data bases

Seminar lectures and exercises on the following topics:

PROGRAMMING:

Introduction (4 hours)
- Computer and information sciences
- Computer architectures and operating systems
- Basics of computer programming and algorithm design
- Boolean algebra and evaluation of predicates

Introduction to the Python programming language: structure and syntax (12 hours)
- Built-in data types
- Variables
- Basic operators
- Input handling
- Conditional execution
- Loops and iterations
- Strings and regular expressions
- Data structures (tuples, lists, sets, dictionaries)

Advanced programming in Python (14 hours)
- Functions
- List comprehension / higher-order functions
- Recursion
- Files management
- Data visualization techniques

Introduction to object-oriented programming (5 hours)
- Concepts (abstraction and composition)
- Objects, classes and packages
- Attributes and methods (with constructors, getters, and setters)
- Inheritance
- Exceptions

DATABASES:

Introduction (2 hours)
· Data versus information. The notions of Information System, Database, and DBMS. Data types, constraints, and data integrity. Queries and applications: transactional and analytical systems. Users, roles, tools and modules of a DBMS.

Relational Theory (6 hours)
· The Relational Data Model: domains, relations, tuples (informal and formal definitions); null values and primary keys.
· Relational Algebra: basic and derived operators. Simple queries.
· Complex queries; query composability and equivalence.

SQL: Structured Query Language (12 hours)
· Definition of domains and tables; primary and foreign key constraints.
· Simple SQL queries (projection, selection, joins, sorting, aggregates).
· Complex queries (set operators, grouping, nesting, views).
· Modifications (of data and schema).
· Advanced schema specification: generic integrity constraints, reaction policies, triggers and procedures (hints).
· Physical data storage, indexing, and query execution cost (hints).

Conceptual and Logical Design (6 hours)
· The Entity-Relationship model: constructs, identifiers, hierarchies and their properties.
· Phases and abstractions in database design (life cycle, strategies, quality measures).
· Logical design: translation principles, hierarchy resolution, management of identifiers, attributes, and associations. Normalization and physical design (hints).

Other Data Models (4 hours)
· Ordered, nested, hierarchical data models. The case of XML.
· Queries and query languages for non-relational data.