Python Automation Hot Selling Course!

Automate Tasks with Python

What you'll learn

Introduction to Python

Write effective Python code

Work with strings and lists

Python in practice

Requirements

some computer knowledge

Description

Automating tasks with Python has revolutionized the way individuals and organizations streamline their workflows. Python's simplicity and versatility make it an ideal choice for automating a wide range of repetitive tasks across various domains. From file management to data processing and web scraping, Python offers an extensive ecosystem of libraries and tools that empower users to automate virtually any task imaginable. With libraries like os and shutil, Python simplifies file manipulation and system-level operations, allowing users to automate tasks such as file renaming, copying, and deletion with just a few lines of code. Furthermore, Python's subprocess module enables seamless integration with external applications, facilitating the automation of complex processes and workflows. For tasks involving web scraping and data extraction, Python's Selenium and Beautiful Soup libraries provide robust solutions, allowing users to automate interactions with web pages and extract data from HTML documents effortlessly. Moreover, Python's PyAutoGUI library enables GUI automation for desktop applications, making it possible to automate mouse and keyboard interactions with graphical interfaces. By leveraging Python's automation capabilities, individuals and organizations can significantly increase productivity, reduce manual errors, and focus on more strategic and creative tasks, ultimately driving efficiency and innovation in their operations. this will help you on your journey

Overview

Section 1: Introduction to Python

Lecture 1 Introduction to Python

Lecture 2 Python Overview

Lecture 3 Healthy habits for course completion

Lecture 4 Introduction to Python Programming

Lecture 5 more on python

Lecture 6 Get to know python

Lecture 7 create basic python script

Lecture 8 Python environments

Section 2: Core Python Components

Lecture 9 Data types in Python

Lecture 10 More about data types

Lecture 11 work with variables

Lecture 12 assign and reassign variables in python

Section 3: conditional and iterative statements

Lecture 13 Conditional statements in Python

Lecture 14 More on conditionals in Python

Lecture 15 For loops

Lecture 16 While loops

Lecture 17 more on loops

Lecture 18 wrap up

Lecture 19 Reference guide: Python concepts from module 1

Lecture 20 Glossary terms from module 1

Section 4: Welcome to module 2

Lecture 21 Introduction to Function

Lecture 22 Create a basic function

Lecture 23 Python functions in cybersecurity

Section 5: work with functions

Lecture 24 Use parameters in functions

Lecture 25 Return statements

Lecture 26 Functions and variables

Lecture 27 Explore built-in functions

Lecture 28 Work with built-in functions

Section 6: Learn from the python community

Lecture 29 Modules and libraries

Lecture 30 Import modules and libraries in Python

Lecture 31 Code readability

Lecture 32 Ensure proper syntax and readability in Python

Lecture 33 Reference guide: Python concepts from module 2

Lecture 34 Glossary terms from module 2

Lecture 35 Wrap-up

Section 7: working with strings

Lecture 36 Welcome to module 3

Lecture 37 String operations

Lecture 38 String indices and slices

Lecture 39 Strings and the security analyst

Section 8: Work with lists and develop algorithms

Lecture 40 List operations in Python

Lecture 41 Write a simple algorithm

Lecture 42 Lists and the security analyst

Lecture 43 Regular expressions in Python

Lecture 44 wrap up

Section 9: Review

Lecture 45 More about regular expressions

Lecture 46 Reference guide: Python concepts from module 3

Section 10: Python for automation

Lecture 47 Welcome to module 4

Lecture 48 Automate tasks with Python

Lecture 49 Glossary terms from module 3

Lecture 50 Essential Python components for automation

Section 11: work with python

Lecture 51 Access a text file in Python

Lecture 52 Import files into Python

Lecture 53 Parse a text file in Python

Lecture 54 Work with files in Python

Lecture 55 Develop a parsing algorithm in Python

Section 12: Debug Python code

Lecture 56 Debugging strategies

Lecture 57 Apply debugging strategies

Lecture 58 Explore debugging techniques

Lecture 59 Wrap-up

Lecture 60 course Wrap-up

Lecture 61 Reference guide: Python concepts from week 4

Lecture 62 Glossary terms from module 4

Lecture 63 Reference guide: Python concepts

Beginner Python Developers curious about data science,security analysts