关于此 专项课程
100% 在线课程

100% 在线课程

立即开始,按照自己的计划学习。
灵活的计划

灵活的计划

设置并保持灵活的截止日期。
中级

中级

Some programming experience and an interest in Clinical Data Science are required.

可选语言

英语(English)

字幕:英语(English)...

您将获得的技能

Implementation ScienceClinical Text MiningR ProgrammingComputational PhenotypingData Quality Assessment
100% 在线课程

100% 在线课程

立即开始,按照自己的计划学习。
灵活的计划

灵活的计划

设置并保持灵活的截止日期。
中级

中级

Some programming experience and an interest in Clinical Data Science are required.

可选语言

英语(English)

字幕:英语(English)...

专项课程 的运作方式

加入课程

Coursera 专项课程是帮助您掌握一门技能的一系列课程。若要开始学习,请直接注册专项课程,或预览专项课程并选择您要首先开始学习的课程。当您订阅专项课程的部分课程时,您将自动订阅整个专项课程。您可以只完成一门课程,您可以随时暂停学习或结束订阅。访问您的学生面板,跟踪您的课程注册情况和进度。

实践项目

每个专项课程都包括实践项目。您需要成功完成这个(些)项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程,则需要在开始之前完成其他所有课程。

获得证书

在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

how it works

此专项课程包含 6 门课程

课程1

Introduction to Clinical Data Science

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....
课程2

Clinical Data Models and Data Quality Assessments

This course aims to teach the concepts of clinical data models and common data models. Upon completion of this course, learners will be able to interpret and evaluate data model designs using Entity-Relationship Diagrams (ERDs), differentiate between data models and articulate how each are used to support clinical care and data science, and create SQL statements in Google BigQuery to query the MIMIC3 clinical data model and the OMOP common data model....
课程3

Identifying Patient Populations

This course teaches you the fundamentals of computational phenotyping, a biomedical informatics method for identifying patient populations. In this course you will learn how different clinical data types perform when trying to identify patients with a particular disease or trait. You will also learn how to program different data manipulations and combinations to increase the complexity and improve the performance of your algorithms. Finally, you will have a chance to put your skills to the test with a real-world practical application where you develop a computational phenotyping algorithm to identify patients who have hypertension. You will complete this work using a real clinical data set while using a free, online computational environment for data science hosted by our Industry Partner Google Cloud....
课程4

Clinical Natural Language Processing

This course teaches you the fundamentals of clinical natural language processing. In this course you will learn practical techniques for extracting information stored in text-based portions of electronic medical records....

讲师

Avatar

Laura K. Wiley, PhD

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

Michael G. Kahn, MD, PhD

Professor of Clinical Informatics
Department of Pediatrics, Anschutz Medical Campus

行业合作伙伴

Industry Partner Logo #0

关于 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....

常见问题

  • 可以!点击您感兴趣的课程卡开始注册即可。注册并完成课程后,您可以获得可共享的证书,或者您也可以旁听该课程免费查看课程资料。如果您订阅的课程是某专项课程的一部分,系统会自动为您订阅完整的专项课程。访问您的学生面板,跟踪您的进度。

  • 此课程完全在线学习,无需到教室现场上课。您可以通过网络或移动设备随时随地访问课程视频、阅读材料和作业。

  • 此专项课程不提供大学学分,但部分大学可能会选择接受专项课程证书作为学分。查看您的合作院校了解详情。

  • Unfortunately at this time we can only allow students who have access to Google services (i.e., 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.

  • The specialization will take approximately 6 months to complete. However students can take the specialization at their own pace.

  • Some experience or awareness of programming and statistical concepts are helpful. However, Course 1 - Introduction to Clinical Data Science, provides learners with enough training in SQL and R to complete the specialization.

  • We highly recommend that you take Course 1 - Introduction to Clinical Data Science, first as it is meant to provide basic training and information useful for Courses 2-6. Although you may take Course 2-6 in any order, it may be helpful to take them sequentially.

还有其他问题吗?请访问 学生帮助中心