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Python (Advanced) Training Course


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Python (Advanced) training course (code: PYTHONADV)

Learn To Produce Better Code, Faster, With Advanced Python Skills


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TRAINING COURSE OVERVIEW

Our Advanced Python training course has had great feeback from Developers, Testers, Data Scientists, Financial modellers and analysts who already use Python on a day-to-day basis, but need to know how to get even more out of the language.

This advanced Python training course will teach you additional  techniques and features relevant to Python to help you realise its full potential as an elegant language for rapid development of test scripts and applications. Python is a dynamic object-oriented programming language. It offers strong support for integration with other development languages and tools, and comes with extensive standard libraries.

Python also serves as a great introduction to Functional Programming, allowing us to explore topics such as closures, comprehensions, generators and decorators. And of course one of the great strengths of Python is the extensive set of libraries.  We take a tour of some of the more interesting libraries and even show how to interface to your own libraries written in C and C++, downloaded from a local repository using PIP.


AUDIENCE

Data Scientists, Analysts, Testers and Programmers who are looking to advance their existing Python skills.



DETAILHIGHLIGHTS

1. Regular Expressions and String Processing

Various advanced examples

2. Advanced Object Orientation

old/new style classes
method lookup and __mro__
inheritance, polymorphism, multiple inheritance
metaprogramming
operator overloading

3. Modern Approaches to Exception Handling

standard exceptions
asserts
controlling tracebacks
logging

4. Installing Packages and Working with Repositories

Anaconda, Pip, Writing your own local repository

5. Agile Development with TDD in Python

TDD examples in PyCharm or Eclipse, Nose, Unit Test

6. Advanced Language Techniques

Decorators, Iterators and Generators

7. Functional Programming

lambda functions
filters and maps
descriptors
nested functions
currying
closures

8. Working with Excel

A brief overview of working with Numpy, Pandas, OpenPyXl, MatplotLib, Using Excel Charts (see Python for Data Scientists for an in depth course in these topics)

9. Networking:

Ftp, Stream Sockets, Datagrams, WebBrowser module

10. Writing High Performance Libraries

Using Cython
Interfacing with C and C++
Measuring performance
Code coverage

11. Web Development

Writing a Python Server (Flask) and interfacing with a browser using JSON, AJAX and JQuery

12. Threads and Concurrency

Threading and Multiprocessing libraries.  GIL

13. Working with Databases

Oracle or MySQL,  SQLAlchemy

 

  • Agile Development with TDD in Python
  • Regular Expressions and String Processing
  • Advanced Object Orientation
  • Modern Approaches to Exception Handling
  • Installing Packages and Working with Repositories
  • GIT
  • Advanced Language Techniques
  • Functional Programming
  • Working with Excel
  • Networking:
  • Writing High Performance Libraries
  • Web Development
  • hreads and Concurrency
  • Working with Databases
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PUBLIC COURSES (LONDON, UK)
 

11th Dec 2017 - 3 days £2000
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