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
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About this Course
최근 조회 14,571회
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.
강의 계획 - 이 강좌에서 배울 내용
주
1완료하는 데 1시간 필요
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!
4 videos (Total 16 min), 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
주
2완료하는 데 1시간 필요
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.
7 videos (Total 35 min), 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
주
3완료하는 데 3시간 필요
Tools: SQL
Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization.
5 videos (Total 18 min), 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
주
4완료하는 데 2시간 필요
Tools: R and the Tidyverse
Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R.
2 videos (Total 6 min), 3 readings, 2 quizzes
3개의 읽기 자료
Working with RMarkdown Documents10m
The Data Scientist's Workflow15m
Note about the Assessment2m
2개 연습문제
Programming Exercises Practice Quiz22m
Week 4 Assessment
4.7
17개의 리뷰50%
이 강좌를 수료한 후 새로운 경력 시작하기
33%
이 강좌를 통해 확실한 경력상 이점 얻기
최상위 리뷰
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.
The material is presented very clearly, and exercises are easy to understand and complete but really test one's knowledge of the material.
강사
Laura K. Wiley, PhD
Assistant ProfessorDivision 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.
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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