Description

Course Description:

The Unlock the power of Python to efficiently gather, process, and analyze data from diverse sources. This course equips you with the skills to extract structured and unstructured data from websites, APIs, databases, and documents using Python libraries like  Learn to clean, transform, and store data for meaningful insights and decision-making. With hands-on projects and real-world examples, you’ll master techniques to automate data collection, perform web scraping, and handle large datasets efficiently, preparing you for careers in data analysis, business intelligence, and data-driven research.

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 Data Extraction with Python Certified Course:

• Data Analyst
• Business Intelligence (BI) Analyst
• Data Engineer (Entry Level)
• Web Scraping Specialist
• Python Developer (Data Focused)
• Market Research Analyst
• Freelance Data Extraction Expert
• Research Assistant

Essential Skills you will Develop Data Extraction with Python Certified Course:

• roficient use of Python for data extraction and automation.
• Web scraping using libraries like BeautifulSoup and Scrapy.
• Automating browser actions and data collection using Selenium.
• Working with APIs to fetch and process data from online sources.
• Extracting and parsing data from JSON, XML, and CSV files.
• Data cleaning and preprocessing using Pandas and NumPy.
• Handling unstructured and semi-structured data efficiently.
• Storing extracted data in databases like MySQL, SQLite, or MongoDB

Tools Covered:

• Python
• BeautifulSoup
• Selenium
• Scrapy
• Requests
• Pandas
• NumPy
• Regular Expressions

Syllabus:

Module 1: Introduction to Data Extraction Overview of data extraction and its applications Types of data: structured, unstructured, semi-structured Introduction to Python for data tasks

Module 2: Python Basics for Data Extraction Python data types, loops, and functions File handling (CSV, TXT, JSON) Error handling and debugging techniques.

Module 3: Web Scraping Fundamentals Understanding HTML, CSS, and DOM structure Introduction to  Extracting data from static web pages.

Module 4: Advanced Web Scraping Handling dynamic websites with   Scraping multiple pages and data tables Pagination and data extraction best practices.

Module 5: Working with APIs Introduction to RESTful APIs Fetching data using Requests library Parsing JSON and XML responses.

Module 6: Data Cleaning and Preprocessing Handling missing values and duplicates Data transformation and normalization Using.

Module 7: Regular Expressions (Regex) Basics of regex patterns Extracting specific data from text Applying regex in real-world scenarios.

Module 8: Data Storage and Management Storing data in CSV, Excel, and databases Introduction to  Connecting Python scripts with databases.

Module 9: Automation and Scheduling Automating data extraction tasks using Python scripts Scheduling scripts with cron jobs or Task Scheduler Logging and error handling for automation.

Module 10: Capstone Project and Real-world Applications End-to-end data extraction project Combining web scraping, API data, and database storage Generating insights and reports from extracted data.

Industry Projects:

• E-commerce Price Monitoring
• Job Portal Data Extraction
• Social Media Data Scraper
• Real Estate Listings Analysis
• News Aggregator Project
• Stock Market Data Extraction
• Web Automation for Data Entry
• API-Based Data Dashboard

Who is this program for?

• Aspiring Data Professionals
• Python Developers
• Business Analysts
• Researchers and Academics
• Freelancers & Entrepreneurs
• Students & Graduates
• Anyone Interested in Data Automation