Academic year
2019/2020 Syllabus of previous years
Official course title
Course code
ET4018 (AF:279125 AR:159556)
On campus classes
ECTS credits
Degree level
Bachelor's Degree Programme
Educational sector code
2nd Term
Course year
Go to Moodle page
The course is optional for the degree program, and its frequency is highly recommended to attend the course of DATA MANAGEMENT [ET4015] in a profitable way.
The course aims to give an overview of the fundamentals and techniques at the base of computational systems.
The main purpose of the course is to introduce students to computational thinking, solving a variety of problems through simple programs developed in Python, a popular high-level programming language.

The course is important and relevant for all students who want to deepen or reinforce the most important basis of computer science and programming, thus getting some basic skills in the field of computer science.
Knowledge and understanding:

- Knowing and understanding the representation of information in computer systems
- Knowing the main components of a computer and their basic operation
- Knowing the principles of structured programming (variables, assignments, conditionals, loops, functions, basic I/O, etc.)
- Knowing and understanding the data types of languages and their manipulation
- Knowing the notion of algorithm with examples

Applying knowledge and understanding:

- Ability to realize simple Python programs for data manipulation
- Ability to debug a simple Python program
No particular prerequisite. In carrying out the program, especially during the practical sessions, it is assumed, however, that the students have a certain familiarity with the use of a personal computer and know the basic concepts of its operation.
Computer fundamentals:
- How computers store and transmit data
- How computer hardware and software operate on data
- How humans use computers to solve problems

The main topics include the notion of computation, problem solving and algorithms, the Python language, simple algorithms and data structures, testing and debugging software.

- "Think Python. How to Think Like a Computer Scientist (2e)".
Allen Downey. Green Tea Press (available online).

- Online resources

- Lecture notes

Other texbooks:
- "Computer Science Illuminated (6e)." 
Nell Dale, John Lewis. Jones & Barlet Learning.
The written exam is organized into two parts.
The first one is concerned with a set of questions aiming to test the proficiency of the student with respect to the various topics of the course and the specific technical terminology.
The second part of the exam is related to the skill assessment, through the solution of exercises on the course subjects.
Theoretical and practical lectures.
Exercise lectures.
Definitive programme.
Last update of the programme: 14/04/2019