This course is aimed to demonstate how principles and methods from data science can be applied in clinical reporting.
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Making Data Science Work for Clinical Reporting
GenentechAbout this Course
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Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Basic experience of data science tools, either R or Python, and have experience in using version control tools, ideally Git.
Approx. 11 hours to complete
English
Skills you will gain
- Github
- Agile Software Development
- R Programming
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Coursera Labs
Includes hands on learning projects.
Learn more about Coursera Labs Intermediate Level
Basic experience of data science tools, either R or Python, and have experience in using version control tools, ideally Git.
Approx. 11 hours to complete
English
Offered by
Syllabus - What you will learn from this course
1 hour to complete
Making Data Science work for clinical reporting
1 hour to complete
4 videos (Total 14 min), 1 reading, 1 quiz
2 hours to complete
The burden of being faultless and transparent
2 hours to complete
23 videos (Total 46 min), 2 readings, 1 quiz
2 hours to complete
Bringing DevOps practices and agile mindset to clinical reporting
2 hours to complete
9 videos (Total 63 min), 1 reading, 2 quizzes
2 hours to complete
Version control and git flows for reproducible clinical reporting
2 hours to complete
18 videos (Total 59 min), 1 reading, 1 quiz
3 hours to complete
Making code reusable and robust in clinical reporting — a call for InnerSourcing
3 hours to complete
16 videos (Total 71 min), 3 readings, 1 quiz
2 hours to complete
Assessing and managing risk
2 hours to complete
5 videos (Total 34 min)
5 minutes to complete
Conclusion
5 minutes to complete
1 video (Total 5 min)
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