COMPUTER PROGRAMMING AND DATA MANAGEMENT - 2

Anno accademico
2022/2023 Programmi anni precedenti
Titolo corso in inglese
COMPUTER PROGRAMMING AND DATA MANAGEMENT - 2
Codice insegnamento
EM1404 (AF:383288 AR:206048)
Modalità
In presenza
Crediti formativi universitari
6 su 12 di COMPUTER PROGRAMMING AND DATA MANAGEMENT
Livello laurea
Laurea magistrale (DM270)
Settore scientifico disciplinare
INF/01
Periodo
2° Periodo
Anno corso
1
Sede
VENEZIA
Spazio Moodle
Link allo spazio del corso
This 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 use a programming language to write scripts and more complex software libraries to handle data, including storage, loading, preparation, processing and visualization.
The course introduces the basics of the design and implementation of data processing software applications and libraries. Data processing is intended as the many activities that can be performed on data through automatic computation, including preprocessing, handling, and analysis.

This course teaches students to define a problem and its solution in terms of data structures and information and to use a programming language to solve it effectively.

The students will achieve the following objectives:

Knowledge: i) learn the basics of data handling and the most common data structures; ii) understand how to interpret and write data handling programs in the Python programming language;

Application of knowledge: i) analyze problems and design formal algorithmic solutions using data structures; ii) translate solutions into computer programs to be applied to data.

Communication: i) generate basic data visualizations for preliminary analysis.
The student must have attended the first module of this course proficiently. Specifically, he/she must already know how to write programs in the Python programming language.
1) Introduction
2) Recap of Python built-in data structures and functions
3) Modules and Object-Oriented python
4) Using the NumPy numerical computing package
5) Using he Pandas library
6) Storing and loading data from different sources
7) Data cleaning and preparation
8) Data wrangling, aggregation and manipulation
9) Plotting and visualization
10) Handling time series
Python for Data Analysis, 2nd Edition, Wes McKinney, O'Reilly Media, Inc., ISBN: 9781491957660
The written exam is aimed at assessing the programming skill and the problem solving capability, through the solution of exercises on the course subjects.
Theoretical and practical lectures.
Exercise lectures.
Inglese
scritto
Programma definitivo.
Data ultima modifica programma: 05/09/2022