About this Course
최근 조회 81,069

다음 전문 분야의 5개 강좌 중 3번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 15시간 필요

권장: 15 hours/week...

영어

자막: 영어, 한국어
Course을(를) 수강하는 학습자
  • Data Scientists
  • Risk Managers
  • Data Analysts
  • Process Analysts
  • Machine Learning Engineers

다음 전문 분야의 5개 강좌 중 3번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

완료하는 데 약 15시간 필요

권장: 15 hours/week...

영어

자막: 영어, 한국어

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 6시간 필요

Nested Data and Nested Iteration

15개 동영상 (총 127분), 9 readings, 3 quizzes
15개의 동영상
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
9개의 읽기 자료
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
1개 연습문제
Optional - What Did You Use to Practice This Week?4m
2
완료하는 데 4시간 필요

Map, Filter, and List Comprehensions

13개 동영상 (총 75분), 5 readings, 3 quizzes
13개의 동영상
Map11m
Filter8m
Conclusion - Map and Filter2m
Introduction - List Comprehensions1m
List Comprehensions9m
List Comprehensions Example 17m
List Comprehensions Example 29m
Conclusion - List Comprehensions1m
Introduction - Zip40
Zip7m
The Hangman Blanked Function13m
Conclusion - Zip1m
5개의 읽기 자료
Introduction: Map, Filter, and List Comprehensions10m
Map10m
Filter10m
List Comprehensions10m
Zip10m
1개 연습문제
Optional - What Did You Use to Practice This Week?4m
3
완료하는 데 6시간 필요

Internet APIs

21개 동영상 (총 118분), 13 readings, 2 quizzes
21개의 동영상
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 APIs49
iTunes API7m
flickr API15m
Conclusion - Practice with REST APIs1m
Fun with the Google Places API19m
Introduction - Final Course Project2m
13개의 읽기 자료
How the Internet Works10m
Anatomy of URLs10m
The HTTP Protocol10m
Using REST APIs10m
Fetching a Page with the requests Module10m
Generating URLs with requests.get10m
Reading API Documentation: Datamuse10m
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
4.7
107개의 리뷰Chevron Right

Data Collection and Processing with Python의 최상위 리뷰

대학: CMOct 10th 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.

대학: SSAug 28th 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

강사

Avatar

Paul Resnick

Michael D. Cohen Collegiate Professor
School of Information
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Jaclyn Cohen

Lecturer
School of Information

미시건 대학교 정보

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....

Python 3 Programming 전문 분야 정보

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....
Python 3 Programming

자주 묻는 질문

  • 강좌에 등록하면 바로 모든 비디오, 테스트 및 프로그래밍 과제(해당하는 경우)에 접근할 수 있습니다. 상호 첨삭 과제는 이 세션이 시작된 경우에만 제출하고 검토할 수 있습니다. 강좌를 구매하지 않고 살펴보기만 하면 특정 과제에 접근하지 못할 수 있습니다.

  • 강좌를 등록하면 전문 분야의 모든 강좌에 접근할 수 있고 강좌를 완료하면 수료증을 취득할 수 있습니다. 전자 수료증이 성취도 페이지에 추가되며 해당 페이지에서 수료증을 인쇄하거나 LinkedIn 프로필에 수료증을 추가할 수 있습니다. 강좌 내용만 읽고 살펴보려면 해당 강좌를 무료로 청강할 수 있습니다.

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