Python (Advanced) training course

• Learn to use various advanced examples of expressions and string processing 
• Use Advanced Object Orientation 
• Acquire skills in modern approaches to exception handling
• Learn to install packages and working with repositories
• Execute Agile development with TDD in Python
• Explore advanced language techniques to learn decorators, iterators and generators
• Learn functional programming methods such as Lambda functions
• Make use of Excel, NumPy, Pandas, OpenPyXl and MatplotLib
• Network with FTP, Stream Sockets, Datagrams and WebBrowser modules
• Write high performance libraries with Cython, C and C++
• Execute web development to write a Python Server and interface with a browser 
• Learn threads, concurrency threading and multiprocessing libraries
• Operate databases such as Oracle, MySQL,  and SQLAlchemy

"I haven't done the Pandas integrated with Python before joining my company. So it's very useful to consolidate my understanding of such skill via this course. The Jupyter notebooks provided will be a valuable resource for revising the materials and are really well laid out." JL, Data Analyst

Our Advanced Python training course has had great feedback 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.