This course is part of the Python 3 Programming Specialization

4.7
stars
3,418 ratings
•
580 reviews

Paul Resnick +1 more instructor

60,412 already enrolled

Offered By

Python 3 Programming SpecializationUniversity of Michigan

About this Course

72,040 recent views

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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

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

Intermediate Level

Approx. 16 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

Flexible deadlines

Reset deadlines in accordance to your schedule.

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

Intermediate Level

Approx. 16 hours to complete

English

Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, Korean, German, Russian, English, Spanish

Instructors

Instructor rating

4.76/5 (367 Ratings)

Paul Resnick

Michael D. Cohen Collegiate Professor

School of Information

331,489 Learners

4 Courses

Jaclyn Cohen

Lecturer

School of Information

314,663 Learners

3 Courses

Offered by

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.

Syllabus - What you will learn from this course

Content Rating97%(7,236 ratings)

Week

Week 1

6 hours to complete

Nested Data and Nested Iteration

In week one the video lectures and activities from the Runestone textbook will cover more complex data structures. By the end of this week, you will have learned how to process json formatted data, traverse nested data using nested iteration, and extract values from nested data.

6 hours to complete

15 videos (Total 127 min), 10 readings, 3 quizzes

15 videos

Introduction to the Specialization11m

How to Use the Interactive Textbook14m

Introduction - Nested Data1m

Nested Lists17m

Nested Dictionaries6m

JSON Format and the JSON Module7m

Conclusion - Nested Data1m

Introduction - Nested Iteration1m

Nested Iteration19m

Structuring Nested Data6m

Shallow Copies7m

Deep Copies10m

Extracting from Nested Data13m

A Worked Example of Nested Iteration6m

Conclusion - Nested Iteration1m

10 readings

Syllabus10m

Help Us Learn More About You!10m

Syllabus10m

Introduction: Nested Data and Nested Iteration10m

Nested Dictionaries10m

Processing JSON Results10m

Nested Iteration10m

Structuring Nested Data10m

Deep and Shallow Copies10m

Extracting from Nested Data10m

1 practice exercise

Optional - What Did You Use to Practice This Week?4m

Week

Week 2

4 hours to complete

Map, Filter, and List Comprehensions

In week two you will be learning more advanced forms of accumulation. By the end of the week, you will have learned how to use the map and filter functions in combination with functions to transform or filter out data and store the resulting data in a new object. You will have also learned how to accumulate data using a list comprehension.

4 hours to complete

13 videos (Total 75 min), 5 readings, 3 quizzes

13 videos

Introduction - Map and Filter1m

Map11m

Filter8m

Conclusion - Map and Filter2m

Introduction - List Comprehensions1m

List Comprehensions9m

List Comprehensions Example 17m

List Comprehensions Example 29m

Conclusion - List Comprehensions1m

Introduction - Zip40s

Zip7m

The Hangman Blanked Function13m

Conclusion - Zip1m

5 readings

Introduction: Map, Filter, List Comprehensions, and Zip10m

Map10m

Filter10m

List Comprehensions10m

Zip10m

1 practice exercise

Optional - What Did You Use to Practice This Week?4m

Week

Week 3

6 hours to complete

Internet APIs

In week three you will learn how to request data from the internet using Application Programming Interfaces (APIs). By the end of the week, you will have learned how to access data from a few APIs, cache data that you have requested, and also learned how to read and work with other APIs that were not touched on in the module.

6 hours to complete

21 videos (Total 118 min), 14 readings, 2 quizzes

21 videos

Introduction - REST APIs2m

URLs, Domain Names, and IP Addresses5m

Routing3m

HTTP: Behind the Scenes5m

URL Query Parameters3m

REST API URLs3m

The requests Module5m

Conclusion - REST APIs2m

Introduction - Using REST APIs1m

Generating URLs with requests.get5m

Reading API Documentation: Datamuse7m

Debugging Calls to requests.get5m

Caching Response Content8m

The requests_with_caching Module8m

Conclusion - Using REST APIs1m

Introduction - Practice with REST APIs49s

iTunes API7m

flickr API15m

Conclusion - Practice with REST APIs1m

Fun with the Google Places API19m

Introduction - Final Course Project2m

14 readings

The Internet: Behind the Scenes10m

Anatomy of URLs10m

The HTTP Protocol10m

Using REST APIs10m

Fetching a Page10m

Generating URLs with requests.get10m

Figuring Out How to Use a REST API10m

Debugging Calls to requests.get10m

Caching Response Content10m

Searching for Media on iTunes10m

Searching for tags on Flickr10m

Unicode for Non-English Characters10m

Course Feedback10m

Keep Learning with Michigan Online10m

Reviews

4.7

580 reviews

5 stars
76.78%
4 stars
17.62%
3 stars
4.18%
2 stars
0.72%
1 star
0.66%

TOP REVIEWS FROM DATA COLLECTION AND PROCESSING WITH PYTHON

by AJul 9, 2020

Very interesting and fine course, in this course I learn how to solve Nested data and new a new thing i.e REST API which seems best in course 3 now I am excited about course 4. Thanking you Michigan

by CMOct 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.

by EWApr 23, 2020

Very good course until the final project. There are a lot of bugs that caused me and what seems like a lot of other students to have to spend a great deal of time on it. This time wasn't productive.

by SSAug 27, 2019

Excellent course which teaches how to process request, extract and process Internet data in a simple and step by step approach. I have gained invaluable skills how to handle large data with Python

View all reviews

About the Python 3 Programming Specialization

This specialization teaches the fundamentals of programming in Python 3. We will begin at the beginning, with variables, conditionals, and loops, and get to some intermediate material like keyword parameters, list comprehensions, lambda expressions, and class inheritance.

You will have lots of opportunities to practice. You will also learn ways to reason about program execution, so that it is no longer mysterious and you are able to debug programs when they don’t work. By the end of the specialization, you’ll be writing programs that query Internet APIs for data and extract useful information from them. And you’ll be able to learn to use new modules and APIs on your own by reading the documentation. That will give you a great launch toward being an independent Python programmer. This specialization is a good next step for you if you have completed Python for Everybody but want a more in-depth treatment of Python fundamentals and more practice, so that you can proceed with confidence to specializations like Applied Data Science with Python. But it is also appropriate as a first set of courses in Python if you are already familiar with some other programming language, or if you are up for the challenge of diving in head-first.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

More questions? Visit the Learner Help Center.

Data Collection and Processing with Python

About this Course