课程信息
专项课程

第 1 门课程(共 6 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

Some programming experience in any language.

完成时间(小时)

完成时间大约为17 小时

建议:4 weeks of study, 1-3 hours/week...
可选语言

英语(English)

字幕:英语(English)

您将学到的内容有

  • 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.

专项课程

第 1 门课程(共 6 门)

100% 在线

100% 在线

立即开始,按照自己的计划学习。
可灵活调整截止日期

可灵活调整截止日期

根据您的日程表重置截止日期。
中级

中级

Some programming experience in any language.

完成时间(小时)

完成时间大约为17 小时

建议:4 weeks of study, 1-3 hours/week...
可选语言

英语(English)

字幕:英语(English)

教学大纲 - 您将从这门课程中学到什么

1
完成时间(小时)
完成时间为 1 小时

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!...
Reading
4 个视频 (总计 16 分钟), 5 个阅读材料, 2 个测验
Video4 个视频
Introduction to Clinical Data Science3分钟
Clinical Data Regulations5分钟
Introduction to the MIMIC-III Data Set4分钟
Reading5 个阅读材料
Introduction to Specialization Instructors5分钟
Course Policies5分钟
Accessing Course Data and Technology Platform15分钟
Regulations and Health Privacy Resources10分钟
MIMIC-III Resources and References10分钟
Quiz2 个练习
Week 1 Practice Quiz12分钟
Week 1 Assessment16分钟
2
完成时间(小时)
完成时间为 1 小时

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. ...
Reading
7 个视频 (总计 35 分钟), 2 个测验
Video7 个视频
Encounters4分钟
Billing Data5分钟
Laboratory Data7分钟
Medication Data7分钟
Clinical Observation Data1分钟
Demographics, Social and Family History2分钟
Quiz2 个练习
Week 2 Practice Quiz8分钟
Week 2 Assessment16分钟
3
完成时间(小时)
完成时间为 3 小时

Tools: SQL

Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization....
Reading
5 个视频 (总计 18 分钟), 6 个阅读材料, 2 个测验
Video5 个视频
Querying Tables with SQL2分钟
Joining Tables with SQL4分钟
Aggregating Data with SQL4分钟
Introduction to Google BigQuery3分钟
Reading6 个阅读材料
Introduction and Learning Objectives for Programming Examples and Exercises5分钟
Guide to Google BigQuery Interface10分钟
Querying and Aggregating Individual Tables with Google BigQuery 45分钟
Querying and Joining Multiple Tables with Google BigQuery30分钟
Joining Tables with SQL15分钟
Note about the Assessment2分钟
Quiz2 个练习
Programming Exercises Practice Quiz24分钟
Week 3 Assessment20分钟
4
完成时间(小时)
完成时间为 2 小时

Tools: R and the Tidyverse

Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R. ...
Reading
2 个视频 (总计 6 分钟), 3 个阅读材料, 2 个测验
Video2 个视频
Introduction to RStudio3分钟
Reading3 个阅读材料
Working with RMarkdown Documents10分钟
The Data Scientist's Workflow15分钟
Note about the Assessment2分钟
Quiz2 个练习
Programming Exercises Practice Quiz22分钟
Week 4 Assessment

讲师

Avatar

Laura K. Wiley, PhD

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

关于 University of Colorado System

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....

关于 Clinical Data Science 专项课程

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....
Clinical Data Science

常见问题

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • 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. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • 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.

还有其他问题吗?请访问 学生帮助中心