Learn BeautifulSoup with online courses and programs

BeautifulSoup tutorial curriculum

Before learners begin a BeautifulSoup tutorial, it’s helpful to have some knowledge of Python, including familiarity with regular expressions, lambda expressions, intuitive functions, and the ability to understand basic code blocks.

Introductory coursework might cover:

• What web scraping is

• What basic DOM structure looks like

• How to navigate an HTML tree

• How to parse raw HTML content

• How to extract text, images, or other content

Mid-level learners might explore more advanced topics, such as:

• Techniques for manipulating BeautifulSoup’s methods and selectors, like using Soup Sieve, the CSS selector library

• Best practices for the handling and management of parsed data

• Guidelines for working with dynamic web pages

• Methods for storing and analyzing data

Advanced learners exploring the capabilities of web scraping tools like BeautifulSoup might learn how to work with APIs and how to translate data into visual outputs or integrate with AI and ML solutions.²

Are you interested in learning more about how to work with data? edX offers a variety of educational opportunities for learners interested in studying this topic, as well as a host of other disciplines. A boot camp can provide flexible hands-on learning for those who want to upskill quickly, while executive education is designed for busy professionals. You can also pursue a more comprehensive curriculum in a bachelor’s degree program or, for more advanced learners, a master’s degree program. Find the right learning path for you.

Explore BeautifulSoup jobs

BeautifulSoup is one of many tools of the trade in the data sciences and web development fields. Professionals in these fields may be tasked with finding, extracting, and using data to draw insights or train machine learning models for applications like business intelligence. Roles in which knowledge of BeautifulSoup can be helpful include:

• Web scraper: Collects data from various sources on the internet.³ A web scraper might be an entry-level position on a data science team. Learners interested in this career path could consider a bachelor’s degree in computer science, data science, or another related field, along with a specific study in the Python programming language.

• Data scientist: Responsible for the design, development, and implementation of predictive models and dashboards, data scientists help deliver data-driven insights.⁴ This is an advanced role that may require a bachelor’s or master’s degree in data science, and experience with data science technologies and applications.

• Customer support engineer: Makes digital and self-service support communication possible.The customer support engineer is a technical role that designs and manages customer-facing technologies like chatbots and search engines.⁵

• Python developer: Specialists in the Python programming language, these developers may use the Python-based library, BeautifulSoup, to perform specific job tasks.⁶ This role might also adapt a BeautifulSoup library to meet specific project needs.⁷ Although the titles and some responsibilities may differ, other developer jobs may be opportunities for Python and BeautifulSoup experts.

Each of these roles will have different education and skills requirements. For example, you may be able to build relevant skills in a data analytics boot camp, or similarly in a coding boot camp if you want to specifically work on your programming skills. However, some employers may seek candidates with a degree depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.

How to use BeautifulSoup in your career

Learning BeautifulSoup can help you become more efficient and more effective in your role. While this tool is most helpful for data science applications, these solutions are not always limited to technology-focused roles.

For example, a marketing or sales professional with a technical aptitude and experience with Python can use BeautifulSoup to gather competitive intelligence, monitor trends, or collect customer data. With a bit of experience, the BeautifulSoup find feature makes it easy to parse specific examples of customer reviews, product descriptions, and other data elements. Alternatively, the BeautifulSoup findall command can parse all instances rather than a first instance or a single instance.

Finance and investing professionals can use BeautifulSoup to gather financial data like stock prices, market trends, and various economic indicators. While visual dashboards are common to present this data, anyone with some technical experience in BeautifulSoup and Python programming can manipulate these tools to fit your unique needs.

Like most programs, the BeautifulSoup documentation provides all the instructions that learners need to customize this library to a specific application.⁸ Learners looking for a Python BeautifulSoup example can find code snippets and instructions in the documentation that allow learners to tailor what data this tool pulls from HTML and XML documents.⁹