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.
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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.
教學大綱 - 您將從這門課程中學到什麼
週
1完成時間為 1 小時
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 個視頻 （總計 16 分鐘）, 5 個閱讀材料, 2 個測驗
4 個視頻
Introduction to Clinical Data Science3分鐘
Clinical Data Regulations5分鐘
Introduction to the MIMIC-III Data Set4分鐘
5 個閱讀材料
Introduction to Specialization Instructors5分鐘
Course Policies5分鐘
Accessing Course Data and Technology Platform15分鐘
Regulations and Health Privacy Resources10分鐘
MIMIC-III Resources and References10分鐘
2 個練習
Week 1 Practice Quiz12分鐘
Week 1 Assessment16分鐘
週
2完成時間為 1 小時
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 個視頻 （總計 35 分鐘）, 2 個測驗
7 個視頻
Encounters4分鐘
Billing Data5分鐘
Laboratory Data7分鐘
Medication Data7分鐘
Clinical Observation Data1分鐘
Demographics, Social and Family History2分鐘
2 個練習
Week 2 Practice Quiz8分鐘
Week 2 Assessment16分鐘
週
3完成時間為 3 小時
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 個視頻 （總計 18 分鐘）, 6 個閱讀材料, 2 個測驗
5 個視頻
Querying Tables with SQL2分鐘
Joining Tables with SQL4分鐘
Aggregating Data with SQL4分鐘
Introduction to Google BigQuery3分鐘
6 個閱讀材料
Introduction and Learning Objectives for Programming Examples and Exercises5分鐘
Guide to Google BigQuery Interface10分鐘
Querying and Aggregating Individual Tables with Google BigQuery 45分鐘
Querying and Joining Multiple Tables with Google BigQuery30分鐘
Joining Tables with SQL15分鐘
Note about the Assessment2分鐘
2 個練習
Programming Exercises Practice Quiz24分鐘
Week 3 Assessment20分鐘
週
4完成時間為 2 小時
Tools: R and the Tidyverse
Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R.
2 個視頻 （總計 6 分鐘）, 3 個閱讀材料, 2 個測驗
3 個閱讀材料
Working with RMarkdown Documents10分鐘
The Data Scientist's Workflow15分鐘
Note about the Assessment2分鐘
2 個練習
Programming Exercises Practice Quiz22分鐘
Week 4 Assessment
4.7
17 個審閱50%
完成這些課程後已開始新的職業生涯
33%
通過此課程獲得實實在在的工作福利
熱門審閱
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.
講師
Laura K. Wiley, PhD
Assistant ProfessorDivision of Biomedical Informatics and Personalized Medicine, Anschutz Medical Campus
關於 科罗拉多大学系统
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.
關於 Clinical Data Science 專項課程
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.
常見問題
我什么时候能够访问课程视频和作业？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
退款政策是如何规定的？
有助学金吗？
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.
還有其他問題嗎？請訪問 學生幫助中心。
