Advanced Clinical Data Science
Master advanced techniques in clinical data analysis, focusing on temporal analysis and research quality.
Master advanced techniques in clinical data analysis, focusing on temporal analysis and research quality.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Clinical Data Science Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.8
(23 ratings)
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Instructors:
English
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What you'll learn
Master advanced clinical data analysis techniques
Develop skills in handling temporal data in healthcare
Learn strategies for managing missing data in clinical research
Understand data quality assessment in EHR-based analyses
Gain expertise in replicable clinical analysis methods
Skills you'll gain
This course includes:
2.4 Hours PreRecorded video
3 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This advanced course focuses on sophisticated clinical data science techniques, emphasizing temporal and research quality analysis. Students learn to handle complex clinical data challenges, including data quality assessment, temporal analysis, and missing data management. The curriculum covers advanced analytical integrity, replicability of EHR-based analyses, and practical applications in healthcare settings. Through hands-on assignments and real-world examples, participants develop skills essential for conducting high-quality clinical research and analysis.
Introduction: Advanced Clinical Data Science
Module 1 · 1 Hours to complete
Tools and Techniques: Temporality
Module 2 · 1 Hours to complete
Tools and Techniques: Missing Data
Module 3 · 1 Hours to complete
Practical Application: Careers in Clinical Data Science
Module 4 · 18 Minutes to complete
Fee Structure
Instructors
Leader in Clinical Informatics and Pediatric Research
Dr. Michael G. Kahn is a distinguished Professor of Pediatrics at the University of Colorado Denver, where he also serves as the Biomedical Informatics Core Director for the Colorado Clinical and Translational Sciences Institute and co-Director of the Colorado Center for Personalized Medicine. As the Director of Research Informatics at Children’s Hospital Colorado, he spearheads initiatives that enhance data integration and research capabilities in pediatric care. Dr. Kahn leads Health Data Compass, a cloud-based research data warehouse that aggregates data from multiple clinical, financial, and research institutions, as well as state and federal sources, facilitating advanced research in healthcare. His research interests primarily focus on data model harmonization and the development of sharable data quality measures within distributed research networks. Through his involvement in various regional, national, and international clinical data research networks, Dr. Kahn is committed to improving healthcare outcomes by leveraging informatics to enhance data accessibility and quality for research purposes.
Innovator in Precision Medicine and Biomedical Informatics
Dr. Laura K. Wiley is an Associate Professor in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus, where she focuses on leveraging electronic health records (EHR) for precision medicine discovery and implementation. With a Ph.D. in Human Genetics from Vanderbilt University, Dr. Wiley has developed computational phenotyping algorithms for EHR-linked biobanks and explored precision dosing of medications like warfarin, particularly in African American populations. She serves as the Chief Data Scientist for Health Data Compass, a cloud-based research data warehouse that integrates data from multiple institutions to enhance clinical research capabilities. Dr. Wiley has been actively involved in various initiatives, including a NIH Cancer Moonshot-funded project aimed at creating comprehensive tobacco cessation services at the University of Colorado Cancer Center. Her contributions to the field are recognized through her leadership roles in the American Medical Informatics Association and her involvement in developing the Coursera Clinical Data Science Specialization, which educates students on clinical research informatics skills. Through her research and teaching, Dr. Wiley is dedicated to advancing the integration of data science in healthcare to improve patient outcomes and foster innovation in medical practices.
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4.8 course rating
23 ratings
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