About this Course
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다음 전문 분야의 6개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

Some programming experience in any language.

완료하는 데 약 11시간 필요

권장: 4 weeks of study, 1-3 hours/week...

영어

자막: 영어

배울 내용

  • Check

    Describe how each type of clinical data are generated, specifically outlining who creates the data, when and why the data are generated.

  • Check

    Write SQL code to combine two or more tables using database joins.

  • Check

    Write R code to manipulate and tidy data including: selecting columns, filtering rows, and joining data sets.

  • Check

    Write markdown formatted text and combine with R code in RMarkdown documents.

다음 전문 분야의 6개 강좌 중 1번째 강좌:

100% 온라인

지금 바로 시작해 나만의 일정에 따라 학습을 진행하세요.

유동적 마감일

일정에 따라 마감일을 재설정합니다.

중급 단계

Some programming experience in any language.

완료하는 데 약 11시간 필요

권장: 4 weeks of study, 1-3 hours/week...

영어

자막: 영어

Course을(를) 수강하는 학습자

  • Pharmacists
  • Scientists
  • Biostatisticians
  • Data Scientists
  • Medical Doctors

강의 계획 - 이 강좌에서 배울 내용

1
완료하는 데 1시간 필요

Welcome to the Clinical Data Science Specialization

4개 동영상 (총 16분), 5 readings, 2 quizzes
4개의 동영상
Introduction to Clinical Data Science3m
Clinical Data Regulations5m
Introduction to the MIMIC-III Data Set4m
5개의 읽기 자료
Introduction to Specialization Instructors5m
Course Policies5m
Accessing Course Data and Technology Platform15m
Regulations and Health Privacy Resources10m
MIMIC-III Resources and References10m
2개 연습문제
Week 1 Practice Quiz12m
Week 1 Assessment16m
2
완료하는 데 1시간 필요

Introduction: Clinical Data

7개 동영상 (총 35분), 2 quizzes
7개의 동영상
Encounters4m
Billing Data5m
Laboratory Data7m
Medication Data7m
Clinical Observation Data1m
Demographics, Social and Family History2m
2개 연습문제
Week 2 Practice Quiz8m
Week 2 Assessment16m
3
완료하는 데 3시간 필요

Tools: SQL

5개 동영상 (총 18분), 6 readings, 2 quizzes
5개의 동영상
Querying Tables with SQL2m
Joining Tables with SQL4m
Aggregating Data with SQL4m
Introduction to Google BigQuery3m
6개의 읽기 자료
Introduction and Learning Objectives for Programming Examples and Exercises5m
Guide to Google BigQuery Interface10m
Querying and Aggregating Individual Tables with Google BigQuery 45m
Querying and Joining Multiple Tables with Google BigQuery30m
Joining Tables with SQL15m
Note about the Assessment2m
2개 연습문제
Programming Exercises Practice Quiz24m
Week 3 Assessment20m
4
완료하는 데 2시간 필요

Tools: R and the Tidyverse

2개 동영상 (총 6분), 3 readings, 2 quizzes
2개의 동영상
Introduction to RStudio3m
3개의 읽기 자료
Working with RMarkdown Documents10m
The Data Scientist's Workflow1시 15분
Note about the Assessment2m
2개 연습문제
Programming Exercises Practice Quiz22m
Week 4 Assessment
4.7
34개의 리뷰Chevron Right

25%

이 강좌를 수료한 후 새로운 경력 시작하기

17%

이 강좌를 통해 확실한 경력상 이점 얻기

Introduction to Clinical Data Science의 최상위 리뷰

대학: FMFeb 12th 2019

Easy to understand, very professional and studying material is clear and relevant. I definitely recommend this course to jump into the clinical and healthcare data science world.

대학: SKJul 10th 2019

I encourage people to take this course.\n\nits real time and it equips with real skill.\n\nthe instructor is also so much great and into the point.

강사

Avatar

Laura K. Wiley, PhD

Assistant Professor
Division of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus

콜로라도 대학교 정보

The University of Colorado is a recognized leader in higher education on the national and global stage. We collaborate to meet the diverse needs of our students and communities. We promote innovation, encourage discovery and support the extension of knowledge in ways unique to the state of Colorado and beyond....

Clinical Data Science 전문 분야 정보

Are you interested in how to use data generated by doctors, nurses, and the healthcare system to improve the care of future patients? If so, you may be a future clinical data scientist! This specialization provides learners with hands on experience in use of electronic health records and informatics tools to perform clinical data science. This series of six courses is designed to augment learner’s existing skills in statistics and programming to provide examples of specific challenges, tools, and appropriate interpretations of clinical data. By completing this specialization you will know how to: 1) understand electronic health record data types and structures, 2) deploy basic informatics methodologies on clinical data, 3) provide appropriate clinical and scientific interpretation of applied analyses, and 4) anticipate barriers in implementing informatics tools into complex clinical settings. You will demonstrate your mastery of these skills by completing practical application projects using real clinical data. This specialization is supported by our industry partnership with Google Cloud. Thanks to this support, all learners will have access to a fully hosted online data science computational environment for free! Please note that you must have access to a Google account (i.e., gmail account) to access the clinical data and computational environment....
Clinical Data Science

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.

  • 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.

궁금한 점이 더 있으신가요? 학습자 도움말 센터를 방문해 보세요.