Regular Expression With Python

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Regular Expression With Python
Published 5/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.18 GB | Duration: 2h 28m
Master pattern matching to efficiently extract, validate, and transform text data for real-world Python applications


What you'll learn
Write powerful pattern-matching expressions
Master regular expressions (regex) in Python
Understand regex syntax and special characters
Process and clean text data efficiently
Validate emails, phone numbers, and passwords
Extract specific information from text files
Build practical Python applications using regex
Use Python's re module effectively
Requirements
Basic Python knowledge (variables, loops, functions)
A computer with Python installed (any version)
No prior regex experience required - we'll start from the basics
Willingness to practice with hands-on exercises
Interest in text processing and pattern matching
Description
Regular Expression with Python.Are you ready to unlock the full potential of text processing and data extraction in Python? "Regular Expression with Python" is your gateway to mastering one of the most powerful tools for working with text data. This course is designed for learners who want to efficiently search, match, and manipulate text using regular expressions (regex) in Python, whether you're a beginner or looking to level up your coding skills.You'll start by understanding the basics of regex syntax, including essential metacharacters like ., *, +, ?,[], ^, and $, as well as special sequences such as \d (digits), \w (word characters), and \s (whitespace)89. Through clear explanations and hands-on examples, you'll learn how to craft powerful patterns to extract emails, validate phone numbers, clean messy data, and much more.The course guides you step-by-step through Python's built-in re module, showing you how to use functions like findall(), search(), split(), and sub() to implement regex solutions in real-world scenarios89. You'll also explore practical tips for debugging and optimizing your patterns.To solidify your knowledge, you'll complete a final project where you apply everything you've learned to solve a real-world text processing challenge. By the end of the course, you'll have the confidence and skills to tackle data extraction, validation, and transformation tasks with ease.What You'll GetLifetime access to engaging video lectures and downloadable resourcesPractical exercises and quizzes to reinforce your learningA hands-on project to showcase your new skillsA certificate of completion to boost your resumeWho Should EnrollPython beginners eager to expand their toolkitData analysts, engineers, and developers working with text dataAnyone preparing for coding interviews or real-world data challengesUnlock the secrets of text manipulation-enroll now in "Regular Expression with Python" and start mastering regex today!
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: Regex 101
Lecture 2 Download Resource
Lecture 3 Simple Pattern
Lecture 4 Exercise
Lecture 5 What is Meta Character and First meta character pipe
Lecture 6 Exercise questions
Lecture 7 dot
Lecture 8 Set of Characters[ ]
Lecture 9 Exercise questions
Lecture 10 Quantifiers (*, +, ?, {n,m})
Lecture 11 Special Sequence Characters (\w, \d, \s, \W, \D, \S)
Lecture 12 Regex Challenge - 1
Lecture 13 What is Regex Challenge - 1
Lecture 14 Regex Challenge -1: Answers Explanation
Lecture 15 Regex Challenge -1 : Answers
Lecture 16 Boundary Matcher in Regex
Lecture 17 Regex Challenge - 2
Lecture 18 Regex Challenge - 2 : Answers
Section 3: Regex with Python
Lecture 19 Introduction to re module
Lecture 20 re.match | match pattern beginning in the string
Lecture 21 re.match | Exercise examples
Lecture 22 re.search | match pattern anywhere in the string
Lecture 23 re.findall | match pattern anywhere in the string with multiple occurrences
Section 4: Bonus
Lecture 24 Bonus Lecture
Python developers looking to enhance their text processing skills,Data scientists who need to clean and extract information from unstructured data,Web developers working with form validation or scraping web content,Automation engineers building scripts for text analysis or transformation


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