Getting Started with Python for Data Scientists 2025
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.
Practical information:
Want to register?
- 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.
- Price: Industry, private sector, profession: € 1300 ; Non profit, government, higher education staff, (Doctoral) students, unemployed: € 585
Schedule: December 4, 8, 11, 15 and 18 2025, from 5.30 pm to 9.30 pm.
Georganiseerd door:
Contents of the course
- 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
objective
The objective of the course is that you are capable of doing data management, visualization and analysis in Python on your own.
Book recommendation
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.
Teacher / speaker
Koen Plevoets is the coordinator of the Master in Statistical Data Analysis and a research consultant at the Department of Translation, Interpreting and Communication, both at 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.
