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Web Scraping for Finance

As companies become more data-driven, an increasing number of use cases are set up where the need to step beyond internal data sources – including publicly available open data, data provided by data brokers, and data stemming from API’s – becomes more apparent. However, the “holy grail” of rich data lies within the wider World Wide Web, as the Internet contains a treasure trove of unstructured data that can be extracted and included in subsequent analysis and decision making processes.

As such, web scraping – the extraction, conversion and management of data from the web – is undergoing a revival. It can be used to extract and scrutinize companies’ financial statements allowing for a more comprehensive assessment of their risk and performance metrics; to scrape massive amounts of data from news to rebalance investment portfolios; to perform competitor analysis; etc.

This intensive, hands-on course covers the definitions and history of web scraping, as well as exploring its current applications and examples from the financial domain. Practical, real-life workshops using Python programming language are applied and results are compared with available commercial products. The links between web scraping and other data science techniques (e.g. web crawling, artificial intelligence, text mining and robotic process automation) are also examined.

The programme concludes by addressing managerial and legal aspects, concerns and challenges that need to be taken into account when setting up web scraping initiatives.

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  • Date:
  •  5th -  6th December 2019
  • Venue:
  • Central London
  • Fee:
  • £1345 per day

This course is also available in Singapore

Who The Course is For

  • Data and analytics heads and project managers
  • IT managers and developers
  • Data scientists, analysts and architects
  • Quant analysts and financial engineers
  • Database administrators
  • Information Security staff
  • Compliance officers
  • Consultants

Learning Objectives

  • Understand what web scraping entails and the use cases it enables (with a focus on finance)
  • Understand the building blocks of the web: HTTP, HTML, and CSS
  • Learn how Python packages (e.g. “Requests”, “BeautifulSoup”) are used to extract data from the web
  • Explore the tools to assist with PDF and other forms of content scraping
  • Learn how to scrape more complex, modern websites with technologies like Selenium
  • Gain insights into open-source and closed-source offerings available for web scraping
  • Examine the links between web scraping and web crawling, AI, text mining, robotic process automation
  • Learn about the key managerial and legal aspects and concerns associated with web scraping projects

Prior Knowledge

  • Basic computer usage and understanding of the web (e.g. HTML and HTTP)
  • Prior programming knowledge (e.g. Python) preferred

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