PYTHON for Science and Engineering: Advanced

In recent years, PYTHON has grown in importance for the areas of numeric simulation and scientific computing. PYTHON is used in a variety of projects (e.g. Numpy, Scipy, Matplotlib), as a scripting language in finite element codes, as a system language in Linux and in web development (e.g. Django).

PYTHON for Science and Engineering: Advanced builds on the basics course and goes into the structure of the language and the data structures in more depth, as well as exploring further aspects of the Python Standard Library. The course also contains brief introductions to modern applications such as data analysis (Pandas) and machine learning. The course contents can also be adapted to particular needs on request.

• Extended object-oriented aspects: inheritance, operator overloading, exceptions
• Functional aspects: lambda operator, map, filter, list comprehensions, iterators, generators
• Modules and namespaces
• Special features of the language: duck typing, docstrings, manipulation of objects and classes on runtime, exceptions
• Data model
• Further topics:
  • Decorators, changing classes on runtime, exec function
  • Advanced file handling: xml, json, yaml
  • Software development: unittest, doctest, Python Debugger
  • Short introduction: numpy
  • Machine learning: keras introduction
  • GUI: tkinter
  • Code optimization: ctypes, Cython

• Persons from the fields of IT, software development, mathematics, engineering and science
• Requirements: basic knowledge of PYTHON