Description

Course Description:

The Regular Expressions with Python Certified Course is designed to help learners master the art of text processing, pattern matching, and data extraction using Python’s module. This course covers everything from the basics of regular expressions to advanced pattern-building techniques, enabling participants to efficiently handle complex string operations and automate repetitive text-based tasks. Learners will explore how to identify patterns, validate data, parse logs, clean data, and extract useful information from unstructured text.

By the end of the course, you’ll be proficient in writing, testing, and optimizing regular expressions to enhance your Python programming skills and apply them in data cleaning, web scraping, and text analytics projects. This course is ideal for developers, data analysts, and automation testers looking to strengthen their data-handling capabilities.

Key Features of Course Divine:

• Collaboration with E‑Cell IIT Tirupati
• 1:1 Online Mentorship Platform
• Credit-Based Certification
• Live Classes Led by Industry Experts
• Live, Real-World Projects
• 100% Placement Support
• Potential Interview Training
• Resume-Building Activities

Career Opportunities After Regular Expressions with Python Certified Course:

• Python Developer
• Data Analyst
• Data Engineer
• Automation Tester
• Web Scraping Specialist
• Machine Learning Engineer
• Cybersecurity Analyst
• Software Quality Engineer
• Bioinformatics Analyst
• Database Administrator
• System Administrator
• AI/NLP Engineer
• ETL Developer
• Technical Support Engineer
• Research Assistant
• Email Filtering Specialist
• SEO Analyst
• Text Mining Specialist
• DevOps Engineer
• Freelance Python Automation

Essential Skills you will Develop Regular Expressions with Python Certified Course:

• Mastery of Regular Expression Syntax
• String Matching & Searching
• Text Validation Techniques
• Data Cleaning & Preprocessing
• Advanced Pattern Building
• Error Handling in Regex
• Python  Module Proficiency
• Automated Text Extraction
• Data Transformation Skills
• Integration with Data Analytics
• Log Analysis Techniques
• Web Scraping Enhancement
• Debugging and Testing Regex Patterns
• NLP Preprocessing
• Automation Skills
• File Handling with Regex
• Performance Optimization
• Problem-Solving & Logical Thinking
• Project Implementation Skills
• Confidence in Real-World

Tools Covered:

• Python Module
• PyCharm / VS Code
• Regex101 / RegExr
• Jupyter Notebook
• pandas Library
• NumPy
• BeautifulSoup
• Requests Library
• CSV & JSON Modules
• Logging Module
• Spyder IDE
• Anaconda Distribution
• Regex Debugger Plugins
• Google Colab
• re.compile() Optimization
• NLP Libraries (NLTK / spaCy)
• Text Editors (Sublime Text / Notepad++)
• Pytest Git & GitHub
• Command Line & Shell

Syllabus:

Module 1: Introduction to Regular Expressions Overview of Regular Expressions and their importance Basic syntax, meta-characters, and literals Installing and setting up Python environment Introduction to the module.

Module 2: Pattern Matching Basics Using  functions Working with special sequences and boundaries Hands-on examples of simple text matches.

Module 3: Character Classes and Quantifiers Defining character sets and ranges Quantifiers Greedy vs. non-greedy matching Building flexible patterns for real-world data

Module 4: Grouping and Capturing Capturing groups and backreferences Named groups and non-capturing groups Extracting matched groups with  Nested and multiple grouping patterns.

Module 5: Substitution and Splitting replacement Splitting strings with regex patterns Data sanitization and text formatting Case conversion and cleanup tasks.

Module 6: Advanced Regex Concepts Lookahead and Lookbehind assertions Conditional matching and atomic grouping Multi-line and dot-all modes Handling complex text and multi-line data.

Module 7: File and Log Data Processing Reading and parsing text files using regex xtracting useful data from system logs Filtering structured text data Automating report generation.

Module 8: Regex with Web and Data Applications Using regex with BeautifulSoup and Requests for web scraping Extracting information from HTML, XML, and JSON data Combining regex with pandas for text cleaning Data extraction from APIs and CSV files.

Module 9: Performance and Debugging Techniques Optimizing regex patterns for speed and readability Avoiding catastrophic backtracking Using online regex testers and IDE plugins Best practices for maintainable regex scripts.

Module 10: Real-World Projects and Case Studies Email, URL, and phone number validation project Log file analysis and data extraction project Web scraping and text mining mini-project Final assessment and certification test.

Industry Projects:

• Email and Phone Number Extraction System
• Log File Analyzer
• Web Scraping with Regex and BeautifulSoup
• Data Cleaning and Validation for CSV Files
• Resume Parser Automation

Who is this program for?

• Python Beginners
• Intermediate Learners
• Data Analysts
• Data Scientists
• Automation Testers
• Web Scraping Specialists
• Software Developers
• Cybersecurity Analysts

How To Apply:

Mobile: 9100348679

Email: coursedivine@gmail.com