Advanced Python Course




This course will build upon the knowledge gained in the introductory Python course and requires basic experience in using the programming language Python.


A voluntary self-assessment test is available in Moodle to evaluate your knowledge level:

This advanced course will teach you the following advanced concepts:


  • The object-oriented programming paradigm: classes & objects, attributes & decorators, type hinting, inheritance & polymorphism, UML diagrams, overloading of methods
  • Advanced string handling with regular expressions
  • Exceptions: catching exceptions withtry/except/finally statement, raising exceptions
  • Parallelism: multithreading vs. -processing, inter-process communication & queues, the global interpreter lock, easy parallelization with joblib
  • Best practices in Python:style guide PEP8, jumpstart: version control with git, structure your project, lintering/testing, documentation automation using docstrings, publishing your project on pypi
  • Debugging & Logging
  • Final project: choose one of three mini project proposals (or choose your own) on which which you'll work in groups and apply everything you've learned so far


A live stream of the Python seminar will be offered. Access to moodle is required for remote participation. Real-time support for remote participants during the seminar would be challenging, but i'll offer to answer your questions via the moodle forum afterwards and during a separate video Q&A session for both remote and local participantson the following Monday after the seminar from 10 am to 12 am. The link can be found in the moodle course.




This course takes place on 8th and 9th October from 9 to 17 in the lecture hall, Rubenowstraße 2b.


Please bring your own notebook along. Please configure the eduroam on your notebook in advance. We will work with the University‘s JupyterHub, which is available via eduroam from a web browser on your notebook.


A limited number of notebooks is available but we advise you to bring your own laptop. Please send an e-mail to fabian.wildeuni-greifswaldde in order to reserve a notebook for the course time if required.




  • M. Lutz, Learning Python: Powerful Object-Oriented Programming, O'Reilly, ISBN: 978-1449355739
  • Y. Hilpisch, Python for Finance: Analyze Big Financial Data, O'Reilly, ISBN: 978-1-491-94528-5
  • L. Ramalho, Fluent Python: Clear, Concise and effective Programming, O'Reilly, ISBN: 978-1-491-9-46008


This Workshop is part of the project Datenkompetenz. You can find futher information here.


Trainer: Fabian Wilde

Date: 8th October (9am - 5pm) and  9th October 2020 (9am - 5 pm)

Location: lecture hall, Rubenowstr. 2b

Participants: 24

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