이 전문 분야 정보

최근 조회 119,521

Ask the right questions, manipulate data sets, and create visualizations to communicate results.

This Specialization covers foundational data science tools and techniques, including getting, cleaning, and exploring data, programming in R, and conducting reproducible research. Learners who complete this specialization will be prepared to take the Data Science: Statistics and Machine Learning specialization, in which they build a data product using real-world data.

The five courses in this specialization are the very same courses that make up the first half of the Data Science Specialization. This specialization is presented for learners who want to start and complete the foundational part of the curriculum first, before moving onto the more advanced topics in Data Science: Statistics and Machine Learning.

학습자 경력 결과
39%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
15%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
완료하는 데 약 5개월 필요
매주 8시간 권장
영어
자막: 영어, 한국어, 아랍어, 프랑스어, 중국어 (간체자), 포르투갈어 (브라질), 베트남어, 스페인어, 일본어, 러시아어...
학습자 경력 결과
39%
이 특화 과정을(를) 수료한 후 새로운 경력을 시작함
15%
급여 인상 또는 승진하기
공유 가능한 수료증
완료 시 수료증 획득
100% 온라인 강좌
지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.
유동적 일정
유연한 마감을 설정하고 유지 관리합니다.
초급 단계
완료하는 데 약 5개월 필요
매주 8시간 권장
영어
자막: 영어, 한국어, 아랍어, 프랑스어, 중국어 (간체자), 포르투갈어 (브라질), 베트남어, 스페인어, 일본어, 러시아어...

이 전문 분야에는 5개의 강좌가 있습니다.

강좌1

강좌 1

The Data Scientist’s Toolbox

4.6
별점
26,297개의 평가
5,467개의 리뷰
강좌2

강좌 2

R 프로그래밍

4.5
별점
17,961개의 평가
3,775개의 리뷰
강좌3

강좌 3

Getting and Cleaning Data

4.6
별점
7,149개의 평가
1,134개의 리뷰
강좌4

강좌 4

탐구 데이터 분석

4.7
별점
5,382개의 평가
775개의 리뷰

제공자:

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자주 묻는 질문

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • 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.

  • 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. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 3-6 months.

  • Some programming experience (in any language) is recommended. We also suggest a working knowledge of mathematics up to algebra (neither calculus or linear algebra are required).

  • Begin by taking The Data Scientist's Toolbox and Introduction to R Programming, in order. The other courses may be taken in any order, and in parallel if desired.

  • Coursera courses and certificates don't carry university credit, though some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • You’ll have a foundational understanding of the field and be prepared to continue studying data science.

  • Yes, you can access the course for free via www.coursera.org/jhu. This will allow you to explore the course, watch lectures, and participate in discussions for free. To be eligible to earn a certificate, you must either pay for enrollment or qualify for financial aid.

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