Getting Started with Python for Data Scientists- M5

DA24-25-M5

Engels

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.

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.

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 2024: December 5, 9, 12, 16 and 19, from 5.30 pm to 9.30 pm

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, Ghent

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

The participation fee is 1000 EUR for participants from the private sector. Reduced prices apply to students and staff from non-profit, social profit, and government organizations.

Industry, private sector, profession*: € 1000
Non profit, government, higher education staff: € 750
(Doctoral) students, unemployed: € 450

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

Registration

To register, add the course below to your shopping cart and proceed to checkout.

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UGent PhD students

Doctoral School pays for your course on the condition that you sign the attendance list for each lesson. If you are absent, please notify our academy in advance by email and provide the necessary documents.

By registering for a course or event organized by the Science Academy, you agree to the cancellation procedure that you can find on our website