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.
Este curso forma parte de Programa Especializado - Python 3 Programming
Data Collection and Processing with Python
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Acerca de este Curso
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Nivel intermedio
Aprox. 16 horas para completar
Sugerido: 17 hours/week
Inglés (English)
Subtítulos: Inglés (English), Coreano
Programa - Qué aprenderás en este curso
6 horas para completar
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 horas para completar
15 videos (Total 127 minutos), 9 lecturas, 3 cuestionarios
15 videos
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 Data1m
9 lecturas
Syllabus10m
Help Us Learn More About You!10m
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 ejercicio de práctica
Optional - What Did You Use to Practice This Week?4m
4 horas para completar
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 horas para completar
13 videos (Total 75 minutos), 5 lecturas, 3 cuestionarios
13 videos
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 lecturas
Introduction: Map, Filter, List Comprehensions, and Zip10m
Map10m
Filter10m
List Comprehensions10m
Zip10m
1 ejercicio de práctica
Optional - What Did You Use to Practice This Week?4m
6 horas para completar
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 horas para completar
21 videos (Total 118 minutos), 13 lecturas, 2 cuestionarios
21 videos
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
13 lecturas
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
Principales revisiones sobre Data Collection and Processing with Python
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.
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
Acerca de Universidad de Míchigan
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.
Acerca de Programa especializado Python 3 Programming
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.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
¿Cuál es la política de reembolsos?
¿Hay ayuda económica disponible?
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