In 1999, Guido Van Rossum submitted a funding proposal to DARPA called "Computer Programming for Everybody", in which he further defined his goals for Python: An easy and intuitive language just as powerful as major competitors

From this starting point, this advanced Python course covers the topics listed below. Advance Python course overview • writing better-structured and more robust code • introducing object-oriented programming • using Python modules • pattern-recognition with Regular Expressions

This guide covers Python from the ground up. You'll start with basic concepts like syntax, variables, and data types, and progress to advanced topics such as object-oriented programming, file handling, and concurrency.

Advanced Programming Topics in Python. A brief introduction to Python Working with the filesystem. Operating system interfaces Programming with Threads Network programming Database interfaces Restricted execution Extensions in C. . This is primarily a tour of the Python library. Everything covered is part of the standard Python distribution.

Successful completion of Python Essentials or equivalent. Basic level familiarity with Linux command line. The Sphinx source code for this curriculum can be found on Github. The latest version this curriculum is published at Read the Docs. It is …

This course is an introduction to Python's more advanced features, with a focus on how they are applied in larger applications and frameworks. The target audience is software developers and anyone who wants to take their Python skills far beyond simple script writing. A …

Python 3 is the future of the Python language and it is this version that has introduced many of the new and improved language and library features (that have admittedly been back ported to Python 2 in many cases).

The course covers topics like classes and objects, I/O handling, data handling, the Python object model, testing and debugging, packages and distribution, iterators and generators, functional programming, metaprogramming, extension programming, concurrency with threads, multiprocessing, and Python 3.

Accelerate your Python programs using proven techniques and design patterns. What is this book about? Python comes with a plethora of tools that enable you to create high-performance and robust programs.

It enables the construction and training of machine learning models by providing a flexible and scalable platform. It simplifies the implementation of complex mathematical computations and optimization algorithms. It supports a wide range of model architectures, including neural networks, for solving various machine learning tasks.