Description
Clinical Data Science Specialization, a clinical data science training course published by Coursera Academy. Are you interested in how data generated by doctors, nurses and the healthcare system can be used to improve future patient care? If so, you may be a clinical data scientist in the future. This specialization gives learners experience using electronic health records and informatics tools to conduct clinical data science. This series of six courses is designed to strengthen existing skills in statistics and programming to provide examples of challenges, tools, and appropriate interpretations of clinical data. By completing this specialization, you will understand the following: 1- understanding the types and structures of electronic health record data, 2- applying basic informatics methods on clinical data, 3- providing appropriate clinical and scientific interpretation of applied analysis, 4- Anticipating obstacles in the implementation of informatics tools in complex clinical environments.
You will demonstrate your mastery of these skills by completing practical projects using real clinical data. This expertise is supported by our industry collaboration with Google Cloud. Thanks to this support, all learners will have access to a fully online data science computing environment for free! Please note that you must have access to a Google account (i.e. Gmail account) to access the clinical data and computing environment. Each specialized course culminates in a final project that is a practical application of the tools and techniques you have learned throughout the course. In these projects you will apply your skills to a real clinical dataset using a free online data science environment fully hosted by Google Cloud.
What you will learn
- Data quality assessment
- Computational phenotyping
- Implementation of science
- R programming
- Clinical text extraction
Who is this course suitable for?
Clinical Data Science Specialization course specifications
- Publisher: Coursera
- teacher : Laura K. Wiley
- English language
- Education level: Intermediate
- Number of courses: 6
- Duration of training: 2 months including 10 hours of work per week
Chapters of the Clinical Data Science Specialization course
Course prerequisites
- 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
Pictures
Sample video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
Introduction to Clinical Data Science
Clinical Data Models and Data Quality Assessments
Identifying Patient Populations
Clinical Natural Language Processing
Predictive Modeling and Transforming Clinical Practice
Advanced Clinical Data Science
File(s) password: www.downloadly.ir
Size
2.73 GB
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