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The Web Scraping Fundamentals: Empowering Data-driven Decision Making course provides participants with essential knowledge and practical skills in web scraping techniques. Through this course, participants will learn how to extract data from websites, harness the power of web scraping tools, and utilize the acquired data for data-driven decision making. This course aims to equip participants with the necessary skills to navigate and extract valuable insights from the vast amount of information available on the web.
By the end of this course, participants will be able to:
- Understand the fundamentals of web scraping and its applications in data-driven decision making.
- Explore web scraping tools and techniques for data extraction from websites.
- Identify and target specific data elements using XPath and CSS selectors.
- Utilize Python libraries such as BeautifulSoup and Scrapy for web scraping.
- Handle common challenges and ethical considerations in web scraping.
- Clean and preprocess scraped data for further analysis.
- Apply data-driven decision making using the acquired web scraped data.
- Duration: 4 weeks
- Format: Online, self-paced
- Prerequisites: Basic knowledge of Python programming language and familiarity with HTML and CSS.
In this module, participants will be introduced to the concept of web scraping and its role in data-driven decision making. They will learn about the benefits and applications of web scraping in various industries. The module will also cover the ethical considerations associated with web scraping.
Participants will explore the step-by-step procedure involved in web scraping in this module. They will gain an understanding of the overall process, including planning the scraping project, identifying target websites, determining the data to be scraped, and defining the data extraction methods. Participants will also learn about considerations such as handling login pages, handling large datasets, and dealing with website restrictions.
Participants will explore different web scraping tools and techniques in this module. They will learn how to use XPath and CSS selectors to target specific data elements on websites. The module will also cover various data extraction methods and best practices for efficient and accurate data retrieval.
This module focuses on web scraping using Python. Participants will learn how to use the BeautifulSoup library to parse HTML and extract data from web pages. They will gain hands-on experience in writing Python code to scrape websites, extract relevant information, and store it in a structured format.
Participants will learn how to extract URLs and email IDs from web pages using web scraping techniques. They will explore different strategies to scrape and collect URLs and email addresses for various purposes, such as data collection or contact information retrieval.
In this module, participants will learn how to scrape images from websites using Python. They will discover techniques to identify and extract images from web pages, and explore methods to save and process the scraped images for further analysis or visualization.
This module focuses on scraping data that is dynamically loaded on a web page using techniques such as AJAX or JavaScript. Participants will learn how to inspect the network requests made by a web page, identify the relevant data sources, and extract the desired data using Python libraries and tools.
In this module, participants will learn how to clean and preprocess the web scraped data to ensure its quality and reliability. They will explore techniques for handling missing data, removing duplicates, and transforming the data into a suitable format for further analysis. Participants will gain insights into data cleaning best practices to enhance the accuracy and validity of the extracted data.
Ethics play a vital role in web scraping. This module focuses on the ethical considerations and legal aspects associated with web scraping. Participants will learn about data privacy, terms of service, and guidelines for responsible web scraping practices. The module will also cover strategies for maintaining ethical standards while extracting and using web data.
In the final module, participants will explore how to leverage the web scraped data for data-driven decision making. They will learn techniques for analyzing and visualizing the scraped data to derive meaningful insights. Participants will also gain an understanding of how web scraping can contribute to data-driven strategies and decision-making processes in various domains.
In this module, participants will apply all the concepts and skills learned throughout the course to complete web scraping projects. They will work on real-world scenarios, identifying suitable websites, defining the scope of the project, implementing the web scraping techniques, and analyzing the extracted data. Participants will gain hands-on experience and practical insights into overcoming challenges and effectively utilizing web scraped data.
Upon successful completion of the course, participants will receive a certificate of achievement, demonstrating their proficiency in web scraping fundamentals for data-driven decision making.
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