Learning objectives
By the end of the course, students will master the main tools for data analysis and numerical calculation. In particular, they will be able to:
(i) analyze data and create control dashboards,
(ii) formalize a problem by schematize it in logical-functional terms,
(iii) define and formalize solving algorithms,
(iv) choose the best tool for solving the problem at a hand,
(v) solve typical engineering and operations research problems numerically.
Prerequisites
The course requires a good knowledge of the main functionality of Excel and basic skills in information science. However, to foster the comprehensions, all topics will be introduced and explained starting from scratch.
Furthermore, as the problems dealt with relate to the field of industrial engineering, passing the following modules is recommended, for a full fruition and access of the contents:
(i) business management and economics,
(ii) operations management,
(iii) methods and models of operational research.
Course unit content
The course introduces the main IT tools needed for data analysis and for the numerical solution of classic engineering and operating research problems. The focus is on an advanced use of Excel 365, and on the creation of applications for science and engineering using Python 3.9 programming language and its main libraries.
Full programme
1 Excel 365 for science and engineering
- Recap on the excel worksheets.
- Recap on baisc formula and references.
- Recap on graphs, plot, and data analysis.
- Some advanced functions, logical functions, lookup functions.
- Logical condition and Conditional formatting.
- Lambda and Let functions, the best way to create your own personalized functions.
- Tables, Data Sorting, Data Filtering, Pivot Table.
- Goal Seeking and the Excel's Solver.
2. Python 3.06 for science and engineering
- Introduction to programming.
- Decision Making.
- Repetitions and interation.
- Basic Functions.
- Advanced types and their methods.
- Lambda functions.
- Functions accepting other function as input.
- Closures: functions returning another function.
- Recursion: functions calling themselves.
- Iterator and Generator.
- Exception management and Code Debugging.
- Object Orienting Programming.
- Methods and magic methods.
- Inheritance and polymorphism.
- Properties.
- Creating user defined structures.
Bibliography
Books on Excel
1) Analisi Dati con Excel 2013, di Francesco Borazzo, edito da Apogeo
2) Excel 2013 The missing manual, by Matthew MacDonald, edited by O’Reilly
Books on Python
1) Pensare in Python, by Allen Downey, edited by O’Reilly
2) Learning Python, by Mark Lutz, edited by O’Reilly
Exercies
1) The Python Workbook, Second Edition, by Ben Stephenson Edited by Springer
2) Excel Workbook, by Ballerini et al., Edited by Egea Editori
Lecturer's teaching handouts (covering both Excel and Python topics) will also be available.
Teaching methods
The course includes both theoretical and practical aspects.
The theoretical part will be done on the blackboard (using coloured chalks) and, next, all the topics covered during the theory lessons will be deepened and operationalized, by means of application examples, developed in the computer labs.
All the material produced in the computer labs will be made available and, as the course progresses, handouts, tutorials and solved exercises (written by the teacher) will be provided to supplement the recommended textbooks.
Assessment methods and criteria
A final 2-hours written text is used to assess the level of the students. This test consists of:
(i) 1-2 exercises on Excel 365, scoring 8-10 points,
(ii) 3-5 exercises on Python, at increasing levels of difficulty, for a total of 20-22 points.
The test is organised so that it can be taken entirely "using paper & pencil", but it is still possible to take it in an electronic format, using a personal laptop.
There is also a compulsory oral test for students who scored between 16 and 19 points in the written test.
Students with a score above 24 are given the opportunity of preparing a final project, discussed in a subsequent oral test, to rise their written mark. This activity is compulsory for those who wish to get a mark above 27.
Other information
About 50% of the lessons will be hold in traditional classrooms, while the remainder will be held in computer labs. For a better understading, students are encouraged to take their laptop also during the theoretical lessons. In additioin, for convenience, students are allowed to use their personal laptop instead of the PCs installed in the labs.
2030 agenda goals for sustainable development
Objective 9: Industry, innovation and infrastructure
