Clinical Data Science
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!
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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!
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.
What's inside
Six courses
Introduction to Clinical Data Science
(0 hours)
Introduction to Clinical Data Science
(0 hours)
Clinical Data Models and Data Quality Assessments
(0 hours)
Clinical Data Models and Data Quality Assessments
(0 hours)
Identifying Patient Populations
(0 hours)
Identifying Patient Populations
(0 hours)
Clinical Natural Language Processing
(0 hours)
Clinical Natural Language Processing
(0 hours)
Predictive Modeling and Transforming Clinical Practice
(0 hours)
Predictive Modeling and Transforming Clinical Practice
(0 hours)
Advanced Clinical Data Science
(0 hours)
Advanced Clinical Data Science
(0 hours)Save this collection
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