The aim of the course is to provide students with the methodological and conceptual tools for the design of algorithms and the implementation of programs for the automatic solution of problems.
Specific goals are the introduction of
- information technology as a discipline for the automatic solution of problems;
- tools and methodologies for the design of algorithms;
- fundamental concepts, methodologies and techniques of programming;
- concepts and methods for the use of programs for data analytics problems
At the end of the course, students will be able to tackle a programming problem in all its parts, namely:
- understand, analyze and formalize the problem
- designing a solution algorithm using iterative techniques
- implement the algorithm in a programming language using suitable data structures
and functions.
- address complex data analytics problems using appropriate libraries
Specific goals are the introduction of
- information technology as a discipline for the automatic solution of problems;
- tools and methodologies for the design of algorithms;
- fundamental concepts, methodologies and techniques of programming;
- concepts and methods for the use of programs for data analytics problems
At the end of the course, students will be able to tackle a programming problem in all its parts, namely:
- understand, analyze and formalize the problem
- designing a solution algorithm using iterative techniques
- implement the algorithm in a programming language using suitable data structures
and functions.
- address complex data analytics problems using appropriate libraries
teacher profile teaching materials
- Problems and algorithms
- Computer architecture
- languages and compilation
- I/O, variables, constants
Operations:
- Data types
- Expressions
- Boolean algebra
Control structures:
- Selection
- Iteration
- Functions
Data structures:
- Array
- Struct
Concetti avanzati:
- Libraries
Programme
Basic concepts:- Problems and algorithms
- Computer architecture
- languages and compilation
- I/O, variables, constants
Operations:
- Data types
- Expressions
- Boolean algebra
Control structures:
- Selection
- Iteration
- Functions
Data structures:
- Array
- Struct
Concetti avanzati:
- Libraries
Core Documentation
A. Bellini, A. Guidi, "Linguaggio C. Una guida alla programmazione con elementi di Python", VI Edizione, McGraw-Hill.Reference Bibliography
A. Bellini, A. Guidi, "Linguaggio C. Una guida alla programmazione con elementi di Python", VI Edizione, McGraw-Hill.Type of delivery of the course
In-person classes and labsAttendance
Attendance is not mandatoryType of evaluation
The exam consists of a written test including programming exercises, multiple choice questions, and theoretical questions regarding the course program to be carried out in the laboratory. In the event of an extension of the health emergency from COVID-19, all the provisions governing the methods for evaluating students will be implemented. teacher profile teaching materials
Problems and algorithms
Computer architecture
Languages and Compilation
I / O, variables and constants
* Operations *
Types of data
Expressions
Boolean algebra
* Control structures *
Selection
Iteration
Functions
* Data structures *
Array
Strings
Matrices
* Advanced concepts *
Integrated development environments
Libraries
File
The course uses the C and Python programming languages.
Programme
* Basic concepts *Problems and algorithms
Computer architecture
Languages and Compilation
I / O, variables and constants
* Operations *
Types of data
Expressions
Boolean algebra
* Control structures *
Selection
Iteration
Functions
* Data structures *
Array
Strings
Matrices
* Advanced concepts *
Integrated development environments
Libraries
File
The course uses the C and Python programming languages.
Core Documentation
A. Bellini, A. Guidi, "Linguaggio C. Una guida alla programmazione con elementi di Python", VI Edizione, McGraw-Hill.Reference Bibliography
Official Python documentation: https://docs.python.org/3/ https://numpy.org/doc/stable/user/index.html https://pandas.pydata.org/docs/getting_started/index.html https://scikit-learn.org/stable/index.html Texts: W. McKinney: "Python for Data Analysis" also available for free online at https://wesmckinney.com/book/ "Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow" by A. Geron "Data science con python. Dai fondamenti al machine learning" by Joel Grus Website with many exercises: https://it.softpython.org/Type of delivery of the course
In-person classes and labsAttendance
Attendance is not mandatoryType of evaluation
The exam consists of a written test including programming exercises, multiple choice questions, theoretical questions regarding the course program to be carried out in the laboratory.