Making Data Science Work for Clinical Reporting

Instructors: Dinakar Kulkarni +6 more

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Skills you'll gain

  •   Medical Privacy
  •   Package and Software Management
  •   Data Quality
  •   Risk Management
  •   R Programming
  •   DevOps
  •   Quality Assurance
  •   Agile Methodology
  •   Version Control
  •   Statistical Reporting
  •   Data Sharing
  •   Maintainability
  •   Clinical Data Management
  •   Clinical Trials
  • There are 7 modules in this course

    By the end of the course, learners will understand what requirements there are in reporting clinical trials, and how they impact on how data science is used. The learner will see how they can work efficiently and effectively while still ensuring that they meet the needed standards.

    The burden of being faultless and transparent

    Bringing DevOps practices and agile mindset to clinical reporting

    Version control and git flows for reproducible clinical reporting

    Making code reusable and robust in clinical reporting — a call for InnerSourcing

    Assessing and managing risk

    Conclusion

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