About this course: 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 Everybody”. 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. This course covers Python 3.
Created by: University of Michigan
Taught by: Charles Severance, Associate Professor
School of Information
| Basic Info | Course 3 of 5 in the 零基础 Python 入门 Specialization |
| Commitment | 6 weeks of study, 2-4 hours/week |
| Language | English |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Getting Started
In this section you will install Python and a text editor. In previous classes in the specialization this was an optional assignment, but in this class it is the first requirement to get started. From this point forward we will stop using the browser-based Python grading environment because the browser-based Python environment (Skulpt) is not capable of running the more complex programs we will be developing in this class.
6 videos, 5 readings
- Reading: Python Textbook
- Reading: Help us learn more about you!
- Video: Welcome to Python - Guido van Rossum
- Reading: Welcome to Python 3
- Reading: Notes on Choice of Text Editor
- Reading: Notice for Auditing Learners: Assignment Submission
- Video: Windows 10: Installing Python and Writing A Program
- Video: Windows: Taking Screen Shots
- Video: Macintosh: Using Python and Writing A Program
- Video: Macintosh: Taking Screen Shots
Graded: Peer Review: Installing and Running Python Screen Shots
WEEK 2
Regular Expressions (Chapter 11)
Regular expressions are a very specialized language that allow us to succinctly search strings and extract data from strings. Regular expressions are a language unto themselves. It is not essential to know how to use regular expressions, but they can be quite useful and powerful.
4 videos, 1 reading
- Video: 11.2 - Extracting Data
- Reading: Python Regular Expression Quick Guide
- Video: Bonus: Office Hours - Den Haag
- Video: Bonus Interview: Bjarne Stroustrup - C++
Graded: Regular Expressions
Graded: Extracting Data With Regular Expressions
WEEK 3
Networks and Sockets (Chapter 12)
In this section we learn about the protocols that web browsers use to retrieve documents and web applications use to interact with Application Program Interfaces (APIs).
7 videos, 1 reading
- Video: 12.2 - Hypertext Transfer Protocol (HTTP)
- Video: Worked Example: Sockets (Chapter 12)
- Reading: If You Want to Learn More
- Video: Bonus: Leonard Kleinrock - The First Two Packets on the ARPANET
- Video: Bonus Video: Robert Cailliau - co-Inventor of the Web
- Video: Bonus: Office Hours - Atlanta GA (Buckhead)
- Video: Fun: Dr. Chuck @ CNN Reading the News
Graded: Networks and Sockets
Graded: Understanding the Request / Response Cycle
WEEK 4
Programs that Surf the Web (Chapter 12)
In this section we learn to use Python to retrieve data from web sites and APIs over the Internet.
8 videos, 1 reading
- Video: 12.4 - Retrieving Web Pages
- Video: Worked Example: Using Urllib (Chapter 12)
- Video: 12.5 - Parsing Web Pages
- Video: Worked Example: BeautifulSoup (Chapter 12)
- Reading: Notes Regarding the Use of BeautifulSoup
- Video: Bonus: Office Hours - Montreal
- Video: Bonus Interview: Tim Berners-Lee - Inventing the Web
- Video: Fun: I Got My Mojo Working - Geneva, Switzerland
Graded: Reading Web Data From Python
Graded: Scraping HTML Data with BeautifulSoup
Graded: Assignment: Following Links in HTML Using BeautifulSoup
WEEK 5
Web Services and XML (Chapter 13)
In this section, we learn how to retrieve and parse XML (eXtensible Markup Language) data.
8 videos
- Video: 13.2 eXtensible Markup Language (XML)
- Video: 13.3 - XML Schema
- Video: 13.4 - Parsing XML
- Video: Worked Example: XML (Chapter 13)
- Video: Interview: Roy Fielding - Understanding the REST Architecture
- Video: Bonus: Office Hours - Boston
- Video: Bonus Video: Ian Horrocks / RDF / OWL (Advanced)
Graded: eXtensible Markup Language
Graded: Extracting Data from XML
WEEK 6
JSON and the REST Architecture (Chapter 13)
In this module, we work with Application Program Interfaces / Web Services using the JavaScript Object Notation (JSON) data format.
12 videos, 2 readings
- Video: Worked Example: JSON (Chapter 13)
- Video: Interview: Douglas Crockford - Discovering JSON
- Video: 13.6 - Service Oriented Approach
- Video: Video: Service Oriented Architectures
- Video: 13.7 - Using Application Programming Interfaces
- Video: Worked Example: GeoJSON API (Chapter 13)
- Video: 13.8 - Securing API Requests
- Video: Worked Example: Twitter API (Chapter 13)
- Video: Bonus: Office Hours - Melbourne, AU
- Video: Bonus: Office Hours - Santa Monica, CA
- Video: Bonus: Class Reunion at Bletchley Park
- Reading: Please Rate this Course on Class-Central
- Reading: Post-Course Survey
Graded: REST, JSON, and APIs
Graded: Extracting Data from JSON
Graded: Using the GeoJSON API
FAQs
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Coursework
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University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
Pricing
| Purchase Course | |
|---|---|
| Access to course materials | Available |
| Access to graded materials | Available |
| Receive a final grade | Available |
| Earn a shareable Course Certificate | Available |
Ratings and Reviews
Excellent course as the previous Python for Everybody courses I have taken before. It gave good understanding on how programming languages interact with web services. On top of this it gives good introduction to API. Examples and assignments really help not only to get theory, but ho to use the knowledge in practice. In addition this helps better to remember the materials of the course. Great initiative and really good introduction to programming which could help to take more advanced courses in data science.
great course! This course taught me a great deal, I learned how to access information on the Internet and I have improved my Python capabilities
Very interesting and useful.
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H
Good intro python and data course