Making Data Science Work for Clinical Reporting
Learn to apply data science principles and tools effectively in clinical trial reporting while maintaining quality and compliance.
Learn to apply data science principles and tools effectively in clinical trial reporting while maintaining quality and compliance.
This comprehensive course demonstrates how to integrate data science methodologies into clinical reporting workflows. Students learn to balance efficient data analysis with regulatory requirements, quality standards, and transparency needs. The curriculum covers version control, reproducible research practices, code reusability, and risk management in clinical trials. Through practical examples and hands-on exercises, participants master the application of modern development practices while ensuring compliance with clinical reporting standards.
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Master data science applications in clinical reporting
Implement version control and Git workflows effectively
Develop robust and reusable code for clinical analysis
Understand quality assurance and validation requirements
Apply DevOps practices in clinical settings
Assess and manage risks in clinical coding
Skills you'll gain
This course includes:
289 Minutes PreRecorded video
7 assignments
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 7 modules in this course
This course bridges the gap between data science and clinical reporting requirements. Through seven comprehensive modules, students learn to apply data science principles while maintaining compliance with clinical trial standards. The curriculum covers essential topics including version control, code quality, risk management, and reproducible research practices. Students gain practical experience with tools like Git and R, while learning to implement DevOps and agile methodologies in a clinical context.
Making Data Science work for clinical reporting
Module 1 · 54 Minutes to complete
The burden of being faultless and transparent
Module 2 · 1 Hours to complete
Bringing DevOps practices and agile mindset to clinical reporting
Module 3 · 2 Hours to complete
Version control and git flows for reproducible clinical reporting
Module 4 · 1 Hours to complete
Making code reusable and robust in clinical reporting — a call for InnerSourcing
Module 5 · 2 Hours to complete
Assessing and managing risk
Module 6 · 2 Hours to complete
Conclusion
Module 7 · 4 Minutes to complete
Fee Structure
Financial Aid
Instructor
Innovator in Meta-Science and Research Methods
Dr. Daniel Lakens is an Associate Professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), where he specializes in meta-science, research methods, and applied statistics. His empirical research primarily explores conceptual thought, similarity, and meaning, while also focusing on the design and interpretation of studies, as well as the development of reward structures within scientific research. Dr. Lakens is committed to enhancing the reliability and efficiency of psychological science, evidenced by his work funded by an NWO VIDI grant aimed at improving research practices. He has been instrumental in advocating for replication research and has co-edited a special issue on pre-registered studies with Brian Nosek. A passionate educator, he teaches an online MOOC titled "Improving Your Statistical Inferences," which has attracted thousands of learners. Recognized for his contributions to open science, Dr. Lakens has conducted over 40 workshops on improving research methodologies and was awarded the TU/e Teacher of the Year in 2014. Through his innovative approaches to research and education, Dr. Lakens continues to influence the landscape of scientific inquiry, promoting transparency and rigor in the field of psychology.
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Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.