Clinical Data Lab: R, EHRs & Applied Biostatistics
Analyze Clinical Data with R
Develop practical skills in applied biostatistics, clinical data analysis, and research data management at Dresden International University (DIU). In Clinical Data Lab, you will use R/RStudio to analyze real-world datasets, interpret results, and present research findings.
Work with electronic health records (EHRs), explore clinical data structures, and apply foundational database and SQL skills. The course connects data cleaning, analysis, and visualization with reproducible research workflows.
Key Facts
Certificate
Without an exam: Certificate of Enrollment
With an exam: ECTS CertificateCourse start
Planned for 2027
Duration
5 months
Course location
Online
Course format
Part-time
Credit points
5 ECTS
Language
English
Course fee
€1,725
Who This Course Is For:
Clinical Data Lab is designed for professionals who want to work more confidently with clinical datasets, including:
- Data scientists and analysts in healthcare and life sciences working with EHRs and real-world data
- Clinical research professionals seeking practical skills in R/RStudio and applied data analysis
- Healthcare professionals and researchers using clinical data to evaluate evidence and inform decisions
Prior experience in data analysis is helpful. If you are unsure whether the course fits your background, contact DIU for advice.
Course Content & Learning Outcomes
Learn to manage, analyze, and interpret clinical datasets with R/RStudio. Topics include electronic health records, data structures, data cleaning and transformation, exploratory analysis, visualization, statistical methods, and reproducible workflows.
Hands-on coding sessions, applied case studies, workshops, guided projects, and discussions connect analytical methods with research practice. You will also consider ethical and regulatory issues in handling clinical data. The sections below outline the course topics, learning outcomes, and teaching approach.
What You Will Cover
- Introduction to R for clinical data analysis
- Data structures and data management in R
- Working with electronic health records (EHRs)
- Data cleaning, transformation, and preprocessing
- Exploratory data analysis and visualization
- Statistical analysis using R
- Reproducible research workflows
- Ethical and regulatory considerations in handling clinical data
What You Will Be Able to Do
After completion, you will be able to:
- Use R to manage and analyze clinical datasets
- Work with real-world data, including EHRs
- Clean, transform, and prepare data for analysis
- Perform exploratory and statistical analyses
- Create reproducible workflows and visualizations
- Interpret results and communicate findings effectively
How You Will Learn
- Hands-on coding sessions in R
- Applied case studies using real-world datasets
- Interactive workshops and exercises
- Guided projects and assignments
- Discussions with faculty and peers
Scientific Director
Dr. Ben M. W. Illigens, MD, MBI
Instructor in Neurology, Beth Israel Deaconess Medical Center Boston, MA United States and Director, German Sites Development Principles and Practice of Clinical Research Harvard T.H. Chan School of Public Health
Managing Director, CEO, D4L data4life gGmbH
Participation Requirements
A relevant academic or professional background is recommended. Prior experience in data analysis is helpful, but previous programming experience is not necessarily required. The course introduces practical R/RStudio workflows using real-world datasets.
When requesting participation, please outline your education and relevant experience in clinical research, biostatistics, or healthcare data. DIU will review your profile and clarify the appropriate next step, which may include a counseling appointment or a course agreement.
You can request participation in this course independently of the M.Sc. pathway. Requirements for a CAS or the modular pathway toward the Clinical Research M.Sc. are assessed separately. DIU individually reviews eligibility and recognition of course credits for the intended qualification. Taking this course does not automatically grant admission to the M.Sc. pathway or guarantee degree credit.
Your Options Beyond the Individual Course
You can take Clinical Data Lab as an individual course. If you are interested in a Certificate of Advanced Studies (CAS), ask DIU to confirm the required course combination and assessments before booking.
A modular pathway toward the Clinical Research M.Sc. is available to eligible participants, subject to an individual assessment of admission requirements and prior learning. Taking this course does not automatically grant admission or guarantee credit toward the degree.
Frequently Asked Questions
Who Is This Course For?
The course is designed for data analysts, clinical research professionals, and healthcare or life sciences researchers who want practical skills in R/RStudio, clinical data management, and applied biostatistics. It focuses on EHRs and real-world datasets.
Can I Take This as an Individual Course?
Yes. You can inquire about Clinical Data Lab as an individual course. For further academic qualifications, you can explore defined course combinations toward a CAS or the modular M.Sc. pathway for eligible participants. DIU reviews the required components and your eligibility separately. Completing this course does not automatically grant admission or guarantee degree credit.
What Will I Learn?
You will learn to manage, clean, analyze, and visualize clinical datasets with R/RStudio. Topics include EHRs, data structures, applied biostatistics, reproducible workflows, and ethical and regulatory considerations. Foundational database and SQL skills support efficient clinical data workflows.
Do I Need Programming Experience?
Not necessarily. Prior experience in data analysis is helpful, but the course introduces practical R/RStudio workflows step by step using real-world datasets. If you are unsure whether your background is suitable, contact DIU before booking.
What Are the Participation Requirements?
A relevant academic or professional background is recommended. DIU reviews your education and experience when you request participation. Requirements for a CAS and a possible modular Master’s pathway are assessed separately from entry to this individual course.
How Will I Learn?
The course is delivered online in English over five months. Learning includes hands-on coding in R, applied case studies with real-world datasets, interactive workshops, guided projects, and discussions with faculty and peers. The next course is planned for 2027; contact DIU for the current schedule.
What Certificate Can I Earn?
Without an exam, participation leads to a Certificate of Enrollment. With an exam, you can earn an ECTS Certificate; the course carries 5 ECTS. A CAS is a separate qualification requiring a defined combination of course components and assessments. Please confirm the requirements for your intended qualification with DIU before booking.
How Do I Request Participation?
Use the existing course inquiry form or contact the Study Advisory Team. Include a brief description of your education and relevant experience, and indicate that you are interested in Clinical Data Lab. If you want to work toward a CAS or explore a modular Master’s pathway, mention this so DIU can advise you on the required next steps.
Personal Advice
