Target audience

This course targets professionals and investigators from diverse areas with little to no Python-programming experience who wish to start using Python for their data manipulation, data exploration or statistical analysis.

Description

Python started off as a general-purpose programming language, but in the last decade it has become a popular environment for data science. The reason is that the community of Python users have recently created useful add-on packages which are suitable for data manipulation, preparation, visualization and analysis. This practical course introduces both base Python and the most important packages in a hands-on way with many exercises.

The contents of the course are:

• Introduction: Python and the Anaconda distribution
• Data types: numbers, strings, lists, tuples, sets and dictionaries
• Automation: control flow and self-defined functions
• Importing data and exporting results
• Managing data with NumPy and pandas
• Graphs with matplotlib and seaborn
• Statistical analysis with statsmodels

The objective of the course is that you are capable of doing data management, visualization and analysis in Python on your own.

Python is an open-source programming language which you can freely download (i.e. the Anaconda distribution). Python version 3 or higher is recommended.

Course prerequisites

The course is open to all interested persons. Knowledge of basic statistical concepts and experience with other programming languages are considered advantages, but not required for learning the Python language.

Exam / Certificate

There is no exam connected to this module. If you attend all five classes you will receive a certificate of attendance via e-mail at the end of the course.

Type of course

This is an on campus course. We offer blended learning options if, exceptionally, you can't attend a session on campus.

Schedule

5 Monday and Thursday evenings in December 2022: December 5, 8, 12, 15 and 19, 2022, from 5.30 pm to 9.30 pm

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, Ghent

Teacher

Dr. Koen Plevoets is a post-doctoral researcher at the Department of Translation, Interpreting and Communication of Ghent University. His research focusses on the cognitive load of interpreters. He obtained his PhD in linguistics in 2008 and he has specialized master’s degrees in Artificial Intelligence and in Statistics. He has over 15 years of experience in categorical data analysis, multivariate statistics and text mining. His interests are visualizations of complex data, for which he uses the open-source programming languages R and Python.

Course material

Acces to Python scripts and data files

Book recommendations

A recommended handbook for further study is 'An introduction to statistics with Python'  by Haslwanter, Thomas (2016), Vienna: Springer. ISBN 978-3-319-28316-6. Please note that you do not need a copy of this book to follow the course.

Fees

A different price applies, depending on your main type of employment.

*If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the module price is taken into account starting from the second enrolment.

Register

Register for this course

UGent PhD students

As UGent PhD student you can incorporate this 'specialist course' in your Doctoral Training Program (DTP). To get a refund of the registration fee from your Doctoral School (DS) please follow these strict rules and take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is November 4, 2022.

Opening a dossier with your DS does not mean that you are enrolled for the course with our academy. You still need to enrol via the registration form on this site.

It is you or your department that pays the fee first to our academy. The Doctoral School refunds that fee to you or your department once the course has ended.