What you’ll learn
- Using and creating iterators
- report block area
- format strings
- Using and building generators
- Useful regular expressions
- Container collections and functions
- Create, install, and deploy packages
- SL based math and statistics with functions
- Work with decorators and solve problems
- Real understanding of how advanced Python design works behind the scenes.
- Get professional, friendly and fast support in the Q&A course if you have any problems during this course.
This course includes:
- 2.5 hours on-demand video
- 1 article
- 8 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of completion
Description
Hello, welcome to the Python Beyond Basics and Intermediate Programming tutorial.
In this course, you will study many of the important topics that are necessary to master in order to create applications of any scale and purpose in the Python programming language.
By the end of this course, you will have advanced concepts that every Python developer should know and how to apply them practically to any area of ​​the Python language.
Even if you are in a field such as data science, web development, or machine learning, it is very important to know all the concepts we will talk about in this course and how to use them theoretically and practically as we want. make the program the way you want it without wasting time and hassle.
We created this course for you if you want to advance your Python career to become a prolific Python programmer.
What topics will we cover in this course?
First we’ll talk about iterators in Python, how to use them, the concepts and functions associated with them, how to create them, and what the purpose of simple creation is.
Iterator in Python is just an object that can be iterated. An object that returns data item by item.
This is the short and simple definition of a Python iterator.
Let’s move on to the second part, which we will talk about.
In the second part, we’ll talk about Python’s scope of all types and how to work with them.
Not all variables or functions can be accessed from anywhere in the program. The part of the program where variables or functions can be accessed is called the scope.
In the next section, we’ll talk about formatting strings to ensure they display as expected. and you’ll study these formatting techniques in detail and add them to your Python string formatting toolkit.
And in part four we learn all about:
What are generators in Python and how are they used?
How to create generator functions and expressions
How the Python fetch statement works and the difference between fetch and return.
How to use multiple Python mining expressions in a generator function.
How to use advanced generation methods in your application.
In the next section, you will learn all about regular expressions in Python.
This is a very important topic and we will talk about it in detail and practically and with deep clarification. In fact, you have all the power of regular expressions, work with re-libraries, do pattern matching, and more.
Regular expressions are basically a tool for matching patterns in text. This is a short and simple definition of a regular expression.
In the following sections, you will master the most commonly used data structures from the Python Collections module.
Basically, collections in Python are containers that are used to store collections of data, e.g. B. List and dictionary. This is the default collection. Several modules have been developed that provide additional data structures for storing data sets. One such module is the Python Collections module.
Collections modules are used to extend the functionality of built-in collection containers.
The next section walks you through packaging a simple Python project. It shows you how to add the necessary files and structure to build the package, how to build the package, and how to use the package.
In the following sections you will master most of the math and statistics modules and related functions.
In simple terms, the Mathematics module provides access to the mathematical functions defined by the C standard, and the Statistics module provides functions to calculate mathematical statistics on numeric data.
Finally, in the last part of this course, you will learn something very important: decoration.
In this section about decorators, we’ll look in detail at what decorators are and how to create and use them.
Simply put, and by definition, a decorator is a function that accepts another function and extends the behavior of the last function without explicitly changing it. He . We made this theme very simple, straightforward and with practical examples to illustrate.
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