This course will prepare you to complete all parts of the Clinical Data Science Specialization. In this course you will learn how clinical data are generated, the format of these data, and the ethical and legal restrictions on these data. You will also learn enough SQL and R programming skills to be able to complete the entire Specialization - even if you are a beginner programmer. While you are taking this course you will have access to an actual clinical data set and a free, online computational environment for data science hosted by our Industry Partner Google Cloud.
Introduction to Clinical Data Science
Introduction to Clinical Data Science
This course is part of Clinical Data Science Specialization
Instructor: Laura K. Wiley, PhD
20,866 already enrolled
Included with 
Gain insight into a topic and learn the fundamentals.
4.5
(406 reviews)
Intermediate level
Recommended experience
Flexible schedule
Approx. 8 hours
Learn at your own pace
89%
Most learners liked this course
What you'll learn
Describe how each type of clinical data are generated, specifically outlining who creates the data, when and why the data are generated.
Write SQL code to combine two or more tables using database joins.
Write R code to manipulate and tidy data including: selecting columns, filtering rows, and joining data sets.
Write markdown formatted text and combine with R code in RMarkdown documents.
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
8 assignments
Taught in English
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This course is part of the Clinical Data Science Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Learn what clinical data science is all about and get access to the free technology environment hosted by Google Cloud!
What's included
4 videos6 readings2 assignments
Clinical data are complex. Walk through the four-W's of clinical data to understand where they come from and what they look like.
What's included
7 videos2 assignments
Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization.
What's included
5 videos6 readings2 assignments
Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R.
What's included
2 videos3 readings2 assignments
Instructor
Instructor ratings
4.6 (104 ratings)Offered by
Recommended if you're interested in Data Analysis
King Abdullah University of Science and Technology
University of Glasgow
Coursera Instructor Network
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Learner reviews
4.5
406 reviews
- 5 stars
68.05%
- 4 stars
22.85%
- 3 stars
4.42%
- 2 stars
2.21%
- 1 star
2.45%
Showing 3 of 406
AL
4
Reviewed on Mar 18, 2020
This was a good general overview however there should have been more of a practice task based system when it came to the coding or make the coding a different segment altogether
RR
5
Reviewed on May 23, 2020
Nice bite sized pieces, with relevant application to querying hospital database using (pre-requisite knowledge) of SQL and R-prog. Definitely useful for my speciality and line of work.
AS
5
Reviewed on Oct 28, 2019
Very nice overview of a very complex topic. Somewhat superficial in some areas, but this is an introduction class and covered everything to an acceptable degree. A very intimidating topic.
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Frequently asked questions
Unfortunately at this time we can only allow students who have access to Google services (e.g., a gmail account) to complete the specialization. This is because we give students access to real clinical data and our privacy protections only allow data sharing through the Google BigQuery environment.
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 enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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.