Genentech
Making Data Science Work for Clinical Reporting
Genentech

Making Data Science Work for Clinical Reporting

Taught in English

Some content may not be translated

1,568 already enrolled

Course

Gain insight into a topic and learn the fundamentals

Dinakar Kulkarni
Kamila Duniec
Kamil Wais

Instructors: Dinakar Kulkarni

Intermediate level

Recommended experience

11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace

Details to know

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Assessments

7 quizzes

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There are 7 modules in this course

In this module we will introduce this course. We will provide context on clinical reporting in general, describing how clinical trials work at a high level, as well as providing resources to learn more. We will then focus on motivating the course, describing the benefits of applying data science in the context of clinical reporting

What's included

4 videos1 reading1 quiz

In this module we explore how data scientists are able to share their work confidently with the right people. We will look at important concepts related to data and results sharing, quality assurance and data access restrictions.

What's included

23 videos2 readings1 quiz

In this module we explore how to make the most out of data science by developing the best mindset.

What's included

9 videos1 reading2 quizzes1 discussion prompt

In this module we introduce the idea of version control, and git in particular. We show how you can use git effectively to manage your code during clinical reporting, and how it can be used as a tool for collaboration. We also look at making an R project in particular reproducible

What's included

18 videos1 reading1 quiz

In this module we will discuss benefits of InnerSourcing, OpenSourcing and developing our own R packages. We will review some of the core principles and tools of R package development. Finally, we will learn how to set up a CI/CD workflow for R package development.

What's included

16 videos3 readings1 quiz1 ungraded lab

In this module we will review the tools and approaches used to understand risk in a codebase used to derive datasets and insights. By the completion of this module you will get some hands on experience applying these principles against a specific open source library.

What's included

5 videos1 quiz1 peer review

In this final module we will briefly review the course, and suggest next steps in your learning journey

What's included

1 video

Instructors

Dinakar Kulkarni
Genentech
1 Course1,568 learners
Kamila Duniec
Genentech
1 Course1,568 learners
Kamil Wais
Genentech
1 Course1,568 learners

Offered by

Genentech

Recommended if you're interested in Data Analysis

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