Module 5 - Getting Started with Python for Data Scientists

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 2023: December 4, 7, 11, 14 and 18, 2023, from 5.30 pm to 9.30 pm

 

Venue

Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Ghent, Building S9, 3th floor, Classroom 3.4

 

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.

Is this your first registration for a Beta Academy course? In that case, you will need to create an account first. Afterward, you will receive a confirmation email to activate your account on the academy platform. You do not have to click on the activation link but can immediately return to your shopping cart to complete your course registration. If you do not receive a confirmation email for your course order, please contact our Academy for Lifelong Learning at ipvw.ices@ugent.be.

Are you currently on the Nova-academy website? To proceed with the registration, simply click on the "More information" box located on the left side.

 

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. Open a dossier on the DS website (Application for Registration) for this course.

Opening a dossier with your DS does not mean that you are enrolled for the course with our academy. You still need to register 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.

 

KMO-portefeuille

Information on "KMO-portefeuille": https://www.ugent.be/nl/opleidingen/levenslang-leren/kmo

 

Organisation

Academy for Lifelong Learning (IPVW)

Faculty of Science

ipvw.ices@ugent.be

Website