This course is aimed to demonstate how principles and methods from data science can be applied in clinical reporting.
Making Data Science Work for Clinical Reporting
Give your career the gift of Coursera Plus with $160 off, billed annually. Save today.
Making Data Science Work for Clinical Reporting
Instructors: Dinakar Kulkarni
1,968 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
11 hours to complete
3 weeks at 3 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
7 quizzes
Taught in English
See how employees at top companies are mastering in-demand skills
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
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
Offered by
Recommended if you're interested in Data Analysis
University of Michigan
Johns Hopkins University
Johns Hopkins University
University of California, Irvine
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
New to Data Analysis? Start here.
Open new doors with Coursera Plus
Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.