COMPUTER PROGRAMMING AND DATA MANAGEMENT - 1 - PRACTICE
- Anno accademico
- 2021/2022 Programmi anni precedenti
- Titolo corso in inglese
- COMPUTER PROGRAMMING AND DATA MANAGEMENT - 1 - PRACTICE
- Codice insegnamento
- EM1404 (AF:358744 AR:188024)
- Lingua di insegnamento
- Inglese
- Modalità
- In presenza
- Crediti formativi universitari
- 0 su 12 di COMPUTER PROGRAMMING AND DATA MANAGEMENT
- Livello laurea
- Laurea magistrale (DM270)
- Settore scientifico disciplinare
- INF/01
- Periodo
- 1° Periodo
- Anno corso
- 1
- Sede
- VENEZIA
- Spazio Moodle
- Link allo spazio del corso
Inquadramento dell'insegnamento nel percorso del corso di studio
This "practice" course covers part of the "quantitative" aspects of the master program, and aims to provide the student with knowledge and skills on the computational aspects fundamental for the data science field.
More specifically, the goal of this course is to teach students how to approach problems with an algorithmic approach. Students will learn some basic techniques for problem solving and how to use a programming language to provide a sound and formal description of a designed problem solution.
More specifically, the goal of this course is to teach students how to approach problems with an algorithmic approach. Students will learn some basic techniques for problem solving and how to use a programming language to provide a sound and formal description of a designed problem solution.
Risultati di apprendimento attesi
The course provides an introduction to the basics of computer science and to programming. Programming is intended as a way to model real-world problems and to design algorithmic solutions to solve them. This course teaches students problem solving techniques and algorithmic thinking. Technical topics cover algorithms, data structures, and Python programming. The course also aims at providing some technical skills about coding/scripting aspects of the R framework.
This practice part of the aims to teach students how to use tools and programming environments, and how to solve simple problems using Python programming language.
This practice part of the aims to teach students how to use tools and programming environments, and how to solve simple problems using Python programming language.
Prerequisiti
No specific pre-requirements.
Contenuti
1. Introduction
2. Python Data Types
3. Simple programs
4. Functions and Conditional Statements
5. Iterative Computation
6. Python Strings
7. Python Lists
8. Python Dictionaries
9. Structuring the code with modules and classes
10. File read and write
11. Introduction to matplotlib
12. Problem Solving and Basic Algorithms
13. From Python to R
2. Python Data Types
3. Simple programs
4. Functions and Conditional Statements
5. Iterative Computation
6. Python Strings
7. Python Lists
8. Python Dictionaries
9. Structuring the code with modules and classes
10. File read and write
11. Introduction to matplotlib
12. Problem Solving and Basic Algorithms
13. From Python to R
Testi di riferimento
- "Think Python. How to Think Like a Computer Scientist (2e)". Allen Downey. Green Tea Press (available online).
- Learning Python. O'Reilly. Mark Lutz.
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. O'Reilly. Wes McKinney
- Learning Python. O'Reilly. Mark Lutz.
- Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. O'Reilly. Wes McKinney
Modalità di verifica dell'apprendimento
The written exam is aimed at assessing the programming skill and the problem solving capability, through the solution of exercises on the course subjects.
Modalità di esame
scritto
Metodi didattici
Practical lectures.
Exercise lectures.
Exercise lectures.
Programma definitivo.
Data ultima modifica programma: 23/04/2021