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University of Michigan

Data Collection and Processing with Python

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.

Status: Web Scraping
Status: Data Processing
IntermediateCourse21 hours

Featured reviews

JA

5.0Reviewed Feb 26, 2021

I thoroughly enjoyed using the Runestone tool to immediately test my knowledge after presenting new concepts, and especially when completing the exercises at the end of each chapter.

DP

4.0Reviewed Feb 4, 2021

Good course like the others in the specialization! I found the end of course project unnecessary difficult because there were some subtle errors from the assessment questions and grader.

AR

5.0Reviewed Jan 24, 2020

Excellent coursework and exercises to learn, especially for beginners -Really liked the presentation and constant support - seems like they know how people think while learning python :)

VE

5.0Reviewed May 16, 2020

I thoroughly enjoyed this course, and found myself often looking forward to Prof. Resnick's jokes. I also came to see the beauty and simplicity of Python. Great course. Great language.

GR

5.0Reviewed Jan 2, 2022

Excellent course. Highly recommended. I learned a lot about parts of Python that I was not previously proficient in. I will definitely use what I learned in a job that I'm just about to start.

AG

5.0Reviewed May 3, 2020

This course provides a very good exposure in Nested Listing and dictionaries.Using REST API and parsing the JSON data.The concepts are explained keeping in mind there use in Industry .Thanks a lot!

AV

5.0Reviewed Aug 9, 2020

Great course for nested data analysis, list comprehension and introduces one into the world of APIs. Lots to learn with special treats in the form of Dr. Resnick's dad jokes (pun intended).

SS

5.0Reviewed Aug 21, 2019

Awesome content and guidance with top of the line applications for application of knowledge acquired throughout the course. It covers the basics and then implements higher order topics over them.

SH

5.0Reviewed Oct 14, 2020

The class is very basic. Excellent for people without a programming background. Slow for those who do, but you can skip through concepts you already understand. The exercises are very useful.

CM

5.0Reviewed Oct 9, 2019

This was a really excellent course. The functional project at the end helped me understand how recommendation systems work and now I'm very excited to try to build a similar system for books I love.

SS

5.0Reviewed Jun 7, 2020

Excellent. I learned a lot of useful information. The videos are good, and the final project put it all together ad a challenging exercise. Worth the time spend, that is for sure.

MI

5.0Reviewed Jan 21, 2021

very good, very intuitive course material. however doing something in full python environment within the course would have been even better. thank you professors and all others from UMich and coursera

All reviews

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Semant Jain, PhD
2.0
Reviewed May 24, 2019
Dixant Bikal Sapkota
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Reviewed Apr 20, 2020
Mark Guimaraes
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Reviewed Jan 30, 2019
Yaacov Teplow-Phipps
4.0
Reviewed Jan 30, 2019
Alexander Amy
5.0
Reviewed Apr 30, 2020
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Reviewed Aug 28, 2019
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Reviewed Apr 20, 2020
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Reviewed May 31, 2020
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Reviewed Apr 20, 2020
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Reviewed Jan 2, 2020
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Reviewed Jan 16, 2019
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Reviewed Mar 4, 2019
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Reviewed Jun 8, 2020
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Reviewed Feb 6, 2019
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Reviewed Mar 18, 2024
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5.0
Reviewed Jun 27, 2019
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5.0
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Reviewed Oct 10, 2019
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5.0
Reviewed Aug 22, 2019