Ateneo - UPO

Introduction to the Python programming language for data analysis, data visualization and the development of simple web applications.

Grus Joel, Data Science from Scratch: First Principles with Python, 2019, O'Reilly Publishing
McKinney W., Python for Data Analysis, O'Reilly, 2013

Basic knowledge of the Python programming language and the use of some packages. Programming skills: the student will learn to independently write simple working Python codes.

Nothing

Laboratory lessons in which students will actively write code together with the teacher, the didactive mode is interactive.

Students with physical disabilities, Learning Disabilities or Special Education Needs can request specific services and tools via the Staff Sviluppo e Coordinamento Carriere e Servizi alle Studentesse e agli Studenti, consulting the University webpage: https://www.uniupo.it/en/services/servicesstudents-physical-or-learning-disabilities Students with disabilities, learning disabilities or special education needs, once they have contacted the University Staff, can refer to the tutor in charge of the course to define the examination modalities, concerning academic aspects.

Individual or group project. The exam is assessed on a pass/fail basis. Students will be deemed to have passed if they produce—either individually or as a group—a web application project for data analysis using Python and are able to explain its functionality during an oral interview.

The Python programming language and its IDEs (Integrated Development Environment).
Pyhton packages: what they are, how to install, import and call them in a script.
Basic Python packages for data manipulation and visualization: Numpy and Matplotlib.
More advanced Python packages for data manipulation and visualization: Pandas, Sklearn, and Seaborn.
Introduction to the Python Streamlit package for creating web applications.

At the end of the course, students will be able to write simple projects in Python for the development of Web applications that perform data analysis and visualization.