The course "Python Laboratory" is an optional "type f" activity, which allows to students to obtain 3 CFU, once a final examination is passed. Participation to the course does not require any particular background knowledge of the software Python. In particular:
- The course is open to all students, but priority is given to the students of the Master’s degree in Economics and of the Master’s degree in Banking and Finance.
- The frequency to the classes is compulsory. Students are required to attend at least 2/3 of the exercise lessons and tutorial activities in order to be admitted to the final evaluation.
The course consists of 18 hours of exercise lessons and tutorial activities (plus 2 hours of final examination) in computer laboratory (50 seats) at the University site of Santa Marta (Verona), to be delivered during the first semester. The course will start if a minimum number of requests will be collected. The calendar of the activities will be available as soon as possible.
Tutor: dott. Jacopo Morabito
Requests for participation will be considered following the registration order. The registration is possible from the 15th of October 2017 to the 3rd of November 2017. Please, register through the elearning platform.
Python is a widely used high-level programming language for general-purpose programming. It is an interpreted language, it has a design philosophy that emphasizes code readability and it has a syntax that allows programmers to express concepts in fewer lines of code than might be used in other languages, allowing new users to learn it in a few days. Python features a dynamic type system and automatic memory management and supports multiple programming paradigms, including object-oriented, imperative, functional programming, and procedural styles. It has a large and comprehensive standard library and it can easily be integrated with other programming languages, in particular with R. Python interpreters are available for many operating systems, allowing Python code to run on a wide variety of systems.
Python has gained wide popularity mainly for its use in the management and analysis of large data sets (data science). Today, R and Python are the two most widely used programming languages among data scientists. Both of them have rapidly advanced over the past few years. For these languages there exist many libraries for collecting, handling, visualizing and analyzing large data volumes and for implementing advanced machine learning models. Python is used in many organizations like NASA, Yahoo and Google. Python is open source and free software and has a community-based development model. Other information can be found at https://www.python.it/ and https://www.python.org/
The program of the course will start with an introduction to the software Python and its main functions. Then, some of the topics encountered in mathematical and statistic courses will be considered, as for example, matrix algebra, optimization and interpolation. Arguments will be presented mainly through examples. The course aims at improving the computational and programming skills of the students and at providing instruments that might be useful for the subsequent thesis work. The activity will allow students to improve the knowledge of a programming language that is highly requested in some sectors of the job market.
|Dmitry Zinoviev||Data Science con Python: dalle stringhe al machine learning, le tecniche essenziali per lavorare sui dati (Edizione 1)||APOGEO||2017||9788850334148|
|Joel Grus||Data Science from Scratch: First Principles with Python (Edizione 1)||O'Reilly Media, Inc.||2015||9781491901410|
|Sarah Guido, Andreas C. Müller||Introduction to Machine Learning with Python (Edizione 1)||O'Reilly Media, Inc.||2016||9781449369880|
|Samir Madhavan||Mastering Python for Data Science (Edizione 1)||Packt Publishing||2015||9781784390150|
|Ahmed Sherif||Practical Business Intelligence (Edizione 1)||Packt Publishing||2016||9781785885433|
|Toby Segaran||Programming Collective Intelligence (Edizione 1)||O'Reilly Media, Inc.||2007||9780596529321|
|Jake VanderPlas||Python Data Science Handbook: Essential Tools for Working with Data (Edizione 1)||O'Reilly Media, Inc.||2016||9781491912126|
|William Wesley McKinney||Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython (Edizione 2)||O'Reilly Media, Inc.||2017||9781491957653|
|Vahid Mirjalili, Sebastian Raschka||Python Machine Learning (Edizione 2)||Packt Publishing||2017||9781787125933|
|Chris Albon||Python Machine Learning Cookbook (Edizione 1)||O'Reilly Media, Inc.||2018||9781491989371|
|Allen B. Downey||Think Stats: Exploratory Data Analysis (Edizione 2)||O'Reilly Media, Inc.||2014||9781491907344|
|Richard Lawson||Web Scraping with Python (Edizione 1)||Packt Publishing||2015||9781782164364|
The final examination will consist in a written exam, with an oral examination if necessary, on the use of the software Python.
Data from AA 2017/2018 are not available yet