Data Representation and Serialization

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. Unlock the power of structured data in this hands-on course on data representation and serialization. You'll learn to confidently navigate a range of data formats like CSV, JSON, YAML, and XML, understanding when and how to use each one effectively. Whether you’re managing datasets or building data-driven applications, mastering these formats is essential for clean, efficient, and interoperable code. The course begins with CSV, diving into the basics before progressing to Python’s csv module and third-party tools like pandas and tablib. Next, you’ll explore JSON, comparing its structure to CSV, then manipulating JSON using Python's standard library and alternatives like simplejson and ujson. Each section provides hands-on experience to help reinforce the material. You’ll then move into YAML, exploring its relationship to JSON and learning to read and write YAML using the PyYAML package. Finally, you’ll tackle XML and HTML, using multiple Python tools including xml, lxml, xmltodict, and BeautifulSoup to parse, write, and analyze structured documents, along with important security considerations. This course is ideal for developers, data professionals, and students looking to build a strong foundation in working with structured data formats. Basic Python knowledge is recommended.

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