This course will prepare you to complete all parts of the Clinical Data Science Specialization. In this course you will learn how clinical data are generated, the format of these data, and the ethical and legal restrictions on these data. You will also learn enough SQL and R programming skills to be able to complete the entire Specialization - even if you are a beginner programmer. While you are taking this course you will have access to an actual clinical data set and a free, online computational environment for data science hosted by our Industry Partner Google Cloud. At the end of this course you will be prepared to embark on your clinical data science education journey, learning how to take data created by the healthcare system and improve the health of tomorrow's patients.
이 강좌는 Clinical Data Science 전문 분야의 일부입니다.
Introduction to Clinical Data Science
제공자:
Learner Career Outcomes
25%
17%
배울 내용
Describe how each type of clinical data are generated, specifically outlining who creates the data, when and why the data are generated.
Write SQL code to combine two or more tables using database joins.
Write R code to manipulate and tidy data including: selecting columns, filtering rows, and joining data sets.
Write markdown formatted text and combine with R code in RMarkdown documents.
Learner Career Outcomes
25%
17%
100% 온라인
다음 전문 분야의 6개 강좌 중 1번째 강좌:
유동적 마감일
중급 단계
Some programming experience in any language.
완료하는 데 약 11시간 필요
영어
강의 계획 - 이 강좌에서 배울 내용
Welcome to the Clinical Data Science Specialization
Learn what clinical data science is all about and get access to the free technology environment hosted by Google Cloud!
Introduction: Clinical Data
Clinical data are complex. Walk through the four-W's of clinical data to understand where they come from and what they look like.
Tools: SQL
Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization.
Tools: R and the Tidyverse
Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R.
Introduction to Clinical Data Science의 최상위 리뷰
Very nice overview of a very complex topic. Somewhat superficial in some areas, but this is an introduction class and covered everything to an acceptable degree. A very intimidating topic.
One great course I will recommend to people. Had the chance to learn so much, especially about the MIMIC III dataset as I am using it for a project in AI. Thank you for this course.
강사
Laura K. Wiley, PhD
Assistant Professor콜로라도 대학교 정보
Clinical Data Science 전문 분야 정보
자주 묻는 질문
강의 및 과제를 언제 이용할 수 있게 되나요?
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.
이 전문 분야를 구독하면 무엇을 이용할 수 있나요?
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.
환불 규정은 어떻게 되나요?
재정 지원을 받을 수 있나요?
I live in an area that restricts access to Google products. Will I be able to complete the specialization?
Unfortunately at this time we can only allow students who have access to Google services (e.g., a gmail account) to complete the specialization. This is because we give students access to real clinical data and our privacy protections only allow data sharing through the Google BigQuery environment.
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