University of Michigan - Data Collection and Processing with Python
5.0 /5- Offered byCoursera
- Public/Government Institute
Data Collection and Processing with Python at Coursera Overview
Duration | 16 hours |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Collection and Processing with Python at Coursera Highlights
- Shareable Certificate Earn a Certificate upon completion
- 100% online Start instantly and learn at your own schedule.
- Course 3 of 5 in the Python 3 Programming Specialization
- Flexible deadlines Reset deadlines in accordance to your schedule.
- Intermediate Level
- Approx. 16 hours to complete
- English Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish
Data Collection and Processing with Python at Coursera Course details
- This course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You'll also learn how to use the Python requests module to interact with REST APIs and what to look for in documentation of those APIs. For the final project, you will construct a ?tag recommender? for the flickr photo sharing site.
- The course is well-suited for you if you have already taken the "Python Basics" and "Python Functions, Files, and Dictionaries" courses (courses 1 and 2 of the Python 3 Programming Specialization). If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this course without taking the previous two.
- This is the third of five courses in the Python 3 Programming Specialization.
Data Collection and Processing with Python at Coursera Curriculum
Nested Data and Nested Iteration
Introduction to the Specialization
How to Use the Interactive Textbook
Introduction - Nested Data
Nested Lists
Nested Dictionaries
JSON Format and the JSON Module
Conclusion - Nested Data
Introduction - Nested Iteration
Nested Iteration
Structuring Nested Data
Shallow Copies
Deep Copies
Extracting from Nested Data
A Worked Example of Nested Iteration
Conclusion - Nested Iteration
Syllabus
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Introduction: Nested Data and Nested Iteration
Nested Dictionaries
Processing JSON Results
Nested Iteration
Structuring Nested Data
Deep and Shallow Copies
Extracting from Nested Data
Optional - What Did You Use to Practice This Week?
Map, Filter, and List Comprehensions
Introduction - Map and Filter
Map
Filter
Conclusion - Map and Filter
Introduction - List Comprehensions
List Comprehensions
List Comprehensions Example 1
List Comprehensions Example 2
Conclusion - List Comprehensions
Introduction - Zip
Zip
The Hangman Blanked Function
Conclusion - Zip
Introduction: Map, Filter, List Comprehensions, and Zip
Map
Filter
List Comprehensions
Zip
Optional - What Did You Use to Practice This Week?
Internet APIs
Introduction - REST APIs
URLs, Domain Names, and IP Addresses
Routing
HTTP: Behind the Scenes
URL Query Parameters
REST API URLs
The requests Module
Conclusion - REST APIs
Introduction - Using REST APIs
Generating URLs with requests.get
Reading API Documentation: Datamuse
Debugging Calls to requests.get
Caching Response Content
The requests_with_caching Module
Conclusion - Using REST APIs
Introduction - Practice with REST APIs
iTunes API
flickr API
Conclusion - Practice with REST APIs
Fun with the Google Places API
Introduction - Final Course Project
The Internet: Behind the Scenes
Anatomy of URLs
The HTTP Protocol
Using REST APIs
Fetching a Page
Generating URLs with requests.get
Figuring Out How to Use a REST API
Debugging Calls to requests.get
Caching Response Content
Searching for Media on iTunes
Searching for tags on Flickr
Unicode for Non-English Characters
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