Basics of Data Science

Course objectives
Data science is the study of extracting value from data. It combines insights, techniques, and tools from several disciplines including, among others, computer science, statistics and applied mathematics. The course is intended to provide students with fundamentals of Data Science presenting both theoretical aspects and some practical examples.
The course targets students from all disciplines and consists of six hours. At the end of the course students will have a basic knowledge and understanding of Data Science fundamentals.

ENTRY REQUIREMENTS
This subject is aimed at students with little or no programming experience. The course is mostly theoretical, though basic Python code will be presented to support the analysis of some real case studies with concrete examples.

Content summary
The course will include the following topics:

Course introduction
Data Science fundamentals
Data Science introduction, current landscape and the role of Data Scientist
Exploratory data analysis and the Data Science process
Programming languages and environments for Data Science
Tools for looking at data (1D datasets) and at relationships (2D datasets)
Overview about Data Science Toolboxes
Jupyter Notebooks and practical examples
Teaching methods
The course is structured with theoretical and practical parts.
Lessons and exercises will be integrated: for each concept we will see theory and practice. Exercises will be assigned to students, carried out at home and discussed in class. All information will be available on the website of the course.

A final test will be used to assess students’ knowledge and understanding of the course topics.

Texts
Probability and statistics for Computer Science, by David Forsyth, Publisher: Springer.
https://link.springer.com/book/10.1007/978-3-319-64410-3
Doing Data Science, by Cathy O’Neil, Rachel Schutt, Publisher(s): O’Reilly Media, Inc. ISBN: 9781449358655

You can contact the instructor at the following email address: sandro.fiore@unitn.it
 

Dates