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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.

Contents and Focus Areas

  • 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

Target Groups and Admission Requirements

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

Dates and Deadlines

Next course date: to be announced

Quick Facts

  • Duration: 16 hours
  • Certificate: Confirmation of participation
  • Language of instruction: German or English
  • Course fees: € 550 (VAT free) or for Bachelor's and Master's students: € 250 (VAT free)
    The course fees include course handouts and refreshments in breaks.
  • Course location: online or in-house training
  • Course times: by agreement

Why you Should Learn PYTHON

  • PYTHON is easy to learn and offers high complexity.
  • You can create connections to fast C/C++ and Fortran libraries.
  • You can produce highly effective codes with little effort.
  • Its high flexibility makes PYTHON ideal for rapid prototyping.

PYTHON and the associated software are free software. This means you will gain a cost-saving alternative to commercial programmes such as MATLAB.

Programme Director

Stefan H. REITERER
Dipl.-Ing. Dr.

Contact

Sarah Meinhardt
BA

TU Graz Life Long Learning
Tel.: +43 316 873 4945
lifelong.learningnoSpam@tugraz.at