Traverse the data analysis pipeline using advanced visualizations in Python, and make machine learning start working for you.
This course will show how one can treat the Internet as a source of data. We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML, and JSON data formats in Python.
This course will cover Chapters 11-13 of the textbook “Python for Informatics”. To succeed in this course, you should be familiar with the material covered in Chapters 1-10 of the textbook and the first two courses in this specialization. These topics include variables and expressions, conditional execution (loops, branching, and try/except), functions, Python data structures (strings, lists, dictionaries, and tuples), and manipulating files.
Week 1: Getting Started
Week 2: Regular Expressions (Chapter 11)
Week 3: Networks and Sockets (Chapter 12)
Week 4: Programs that Surf the Web (Chapter 12)
Week 5: Web Services and XML (Chapter 13)
Week 6: JSON and the REST Architecture (Chapter 13)
Using Python to Access Web Data is course 3 of 5 in the Python for Everybody Specialization.
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.