Tools for Numerical and Spatial Data Analysis is a cross-curricular teaching in the different fields of Engineering whose main objective is to make students, future engineers, capable of analyzing and processing a large amount of both numerical and spatial data. Achieving this goal requires the acquisition of a set of skills that will be transmitted to the student and that can be applied to the different fields of engineering.
As part of this path, the teaching aims to provide 1) the ability to use programming languages for numerical analysis; 2) the ability to analyze large masses of data characterized by high sampling frequency and both temporal and spatial extension; 3) the knowledge of data cleaning, data filtering, data transformation and data mining techniques of databases; 4) knowledge of spatial data and transformation and relation operators; 5) the ability to use software for visualization and processing of spatial data (QGIS); 6 ) the knowledge and ability to store, manipulate and query large masses of data by means of the use of relational and spatial databases (SQL);
Upon completion of the course, students will be able to 1) use some programming tools widely used in science; 2) analyze large databases through specific processing techniques; 3) use data processing techniques for information retrieval; 4) know the operators and transformation functions on spatial data for spatial information analysis; 5) manipulate and analyze spatial data through specialized software; and 6) know and be able to use databases for storing, querying and processing information;
As part of this path, the teaching aims to provide 1) the ability to use programming languages for numerical analysis; 2) the ability to analyze large masses of data characterized by high sampling frequency and both temporal and spatial extension; 3) the knowledge of data cleaning, data filtering, data transformation and data mining techniques of databases; 4) knowledge of spatial data and transformation and relation operators; 5) the ability to use software for visualization and processing of spatial data (QGIS); 6 ) the knowledge and ability to store, manipulate and query large masses of data by means of the use of relational and spatial databases (SQL);
Upon completion of the course, students will be able to 1) use some programming tools widely used in science; 2) analyze large databases through specific processing techniques; 3) use data processing techniques for information retrieval; 4) know the operators and transformation functions on spatial data for spatial information analysis; 5) manipulate and analyze spatial data through specialized software; and 6) know and be able to use databases for storing, querying and processing information;
teacher profile teaching materials
As part of this path, the teaching aims to provide 1) the ability to use programming languages for numerical analysis; 2) the ability to analyze large masses of data characterized by high sampling frequency and both temporal and spatial extension; 3) the knowledge of data cleaning, data filtering, data transformation and data mining techniques of databases; 4) knowledge of spatial data and transformation and relation operators; 5) the ability to use software for visualization and processing of spatial data (QGIS); 6 ) the knowledge and ability to store, manipulate and query large masses of data by means of the use of relational and spatial databases (SQL);
Reference bibliography:
• *Python: Guida alla sintassi, alle funzionalità avanzate e all'analisi dei dati* – N. Ceder - Apogeo
• *PostgreSQL: Up and Running* - R.O. Obe, L.S. Hsu – O’REILLY
• *PostGIS in Action* – R.O. Obe, L.S. Hsu - Manning
• *Python Geospatial Development* – W. Westra - PACKT
Programme
Tools for Numerical and Spatial Data Analysis is a cross-curricular teaching in the different fields of Engineering whose main objective is to make students, future engineers, capable of analyzing and processing a large amount of both numerical and spatial data. Achieving this goal requires the acquisition of a set of skills that will be transmitted to the student and that can be applied to the different fields of engineering.As part of this path, the teaching aims to provide 1) the ability to use programming languages for numerical analysis; 2) the ability to analyze large masses of data characterized by high sampling frequency and both temporal and spatial extension; 3) the knowledge of data cleaning, data filtering, data transformation and data mining techniques of databases; 4) knowledge of spatial data and transformation and relation operators; 5) the ability to use software for visualization and processing of spatial data (QGIS); 6 ) the knowledge and ability to store, manipulate and query large masses of data by means of the use of relational and spatial databases (SQL);
Core Documentation
Handouts prepared by the teacher;Reference bibliography:
• *Python: Guida alla sintassi, alle funzionalità avanzate e all'analisi dei dati* – N. Ceder - Apogeo
• *PostgreSQL: Up and Running* - R.O. Obe, L.S. Hsu – O’REILLY
• *PostGIS in Action* – R.O. Obe, L.S. Hsu - Manning
• *Python Geospatial Development* – W. Westra - PACKT
Attendance
Attendance is not mandatory; however, it is strongly recommended due to the requirement to complete a project and the substantial number of exercises planned throughout the course.Type of evaluation
An oral test will be given at the end of the course in which the topics covered in the program will be discussed with the lecturer. During the course it is planned to carry out project which will be discussed in the oral. teacher profile teaching materials
As part of this path, the teaching aims to provide 1) the ability to use programming languages for numerical analysis; 2) the ability to analyze large masses of data characterized by high sampling frequency and both temporal and spatial extension; 3) the knowledge of data cleaning, data filtering, data transformation and data mining techniques of databases; 4) knowledge of spatial data and transformation and relation operators; 5) the ability to use software for visualization and processing of spatial data (QGIS); 6 ) the knowledge and ability to store, manipulate and query large masses of data by means of the use of relational and spatial databases (SQL);
Reference bibliography:
• *Python: Guida alla sintassi, alle funzionalità avanzate e all'analisi dei dati* – N. Ceder - Apogeo
• *PostgreSQL: Up and Running* - R.O. Obe, L.S. Hsu – O’REILLY
• *PostGIS in Action* – R.O. Obe, L.S. Hsu - Manning
• *Python Geospatial Development* – W. Westra - PACKT
Programme
Tools for Numerical and Spatial Data Analysis is a cross-curricular teaching in the different fields of Engineering whose main objective is to make students, future engineers, capable of analyzing and processing a large amount of both numerical and spatial data. Achieving this goal requires the acquisition of a set of skills that will be transmitted to the student and that can be applied to the different fields of engineering.As part of this path, the teaching aims to provide 1) the ability to use programming languages for numerical analysis; 2) the ability to analyze large masses of data characterized by high sampling frequency and both temporal and spatial extension; 3) the knowledge of data cleaning, data filtering, data transformation and data mining techniques of databases; 4) knowledge of spatial data and transformation and relation operators; 5) the ability to use software for visualization and processing of spatial data (QGIS); 6 ) the knowledge and ability to store, manipulate and query large masses of data by means of the use of relational and spatial databases (SQL);
Core Documentation
Handouts prepared by the teacher;Reference bibliography:
• *Python: Guida alla sintassi, alle funzionalità avanzate e all'analisi dei dati* – N. Ceder - Apogeo
• *PostgreSQL: Up and Running* - R.O. Obe, L.S. Hsu – O’REILLY
• *PostGIS in Action* – R.O. Obe, L.S. Hsu - Manning
• *Python Geospatial Development* – W. Westra - PACKT
Attendance
Attendance is not mandatory; however, it is strongly recommended due to the requirement to complete a project and the substantial number of exercises planned throughout the course.Type of evaluation
An oral test will be given at the end of the course in which the topics covered in the program will be discussed with the lecturer. During the course it is planned to carry out project which will be discussed in the oral.