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Laura K. Wiley, PhD
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.
Read more
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.
Read more
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.
At the end of this course you will be prepared to embark on your clinical data science education journey, learning how to take data created by the healthcare system and improve the health of tomorrow's patients.
Register for this course and see more details by visiting:
OpenCourser.com/course/0u98hb/introduction
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What's inside
Syllabus
Welcome to the Clinical Data Science Specialization
Learn what clinical data science is all about and get access to the free technology environment hosted by Google Cloud!
Read more
Syllabus
Welcome to the Clinical Data Science Specialization
Learn what clinical data science is all about and get access to the free technology environment hosted by Google Cloud!
Read more
Introduction: Clinical Data
Clinical data are complex. Walk through the four-W's of clinical data to understand where they come from and what they look like.
Tools: SQL
Develop basic skills in SQL (Structured Query Language) and query the real clinical data set used in the Clinical Data Science Specialization.
Tools: R and the Tidyverse
Learn how to use the tidyverse to implement your Clinical Data Science Workflow in R.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Prepares learners to complete other courses in the Clinical Data Science Specialization
Assists learners who have little to no programming experience
Introduces SQL and R programming skills, which are essential for data science
Provides access to an actual clinical data set and a free, online computational environment for data science
Taught by an experienced instructor with a PhD in Clinical Psychology
Save this course
Save Introduction to Clinical Data Science to your list so you can find it easily later:
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Reviews summary
Clinical data science for health professionals
Learners say that "Introduction to Clinical Data Science" is largely positive. This course provides an excellent introduction to SQL and R programming, which learners describe as engaging and well-structured. Students with no prior experience should expect to dedicate additional time and effort because the course does not provide basic tutorials on R programming. Overall, students highly recommend this course as a starting point for learning about clinical data science.
Students appreciate the real-world clinical data and practical exercises that allow them to apply their learning.
"I was able to learn and practice SQL and R using Google BigQuery on Google Cloud, and used real-world clinical database."
"Very good intro and topics. Good combination of R and SQL and Big Query. Enjoyed it."
"Nice bite sized pieces, with relevant application to querying hospital database using (pre-requisite knowledge) of SQL and R-prog."
The course structure is well-organized and easy to follow.
"The introduction to R is confusing"
"Overall, good ! The introduction to R is confusing"
"A good overview of Clinical Data Science."
"It lays the foundation for more advanced topics."
The course is accessible to learners with no prior knowledge of clinical data science.
"A good overview of Clinical Data Science."
"It lays the foundation for more advanced topics."
"I like this course very much - it gives a structured way to understand clearly and logically about the Clinical Data."
Some students report that the course content and tutorials are outdated.
"the tutorials are outdated, the documentation is not enough when it comes to learning R."
"Some of the screenshots from this course have not been updated for a long time and can cause confusion when trying to follow the steps of the related materials."
Students with no prior experience in R programming may find the course challenging.
"The 3rd and 4th weeks were promoted as applying SQL & R to what basics we have learned. Regrettably for the same, as a visual learner reading the given material did not help much, my background in C.S. helped me better understand SQL, however, that was not the case for R.
I had no prior knowledge of R and I was hoping to be taught at least the basics but what was given was one long document which was troublesome to understand."
"This course requires you to have a foundation in R programming and will not provide much guidance to it."
"In general, a good introductory course to the topic "clinical data" itself, BUT in particular Week 4 was very disappointing to me: An R-One-Pager has been provided which should be the basis for all R exercises."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Clinical Data Science with these
activities:
Find a mentor who works in the field of clinical data science
Show steps
This activity will provide you with guidance and support from an experienced professional.
Show steps
-
Network with people in your field
-
Attend industry events
-
Reach out to potential mentors and ask for their guidance
Review SQL basics
Show steps
Refresh your knowledge of SQL before starting the course to strengthen your foundational understanding of data querying.
Browse courses on
SQL
Show steps
-
Review SQL syntax and commands
-
Practice writing basic SQL queries
-
Complete online tutorials or exercises on SQL
Review concepts of clinical data
Show steps
This activity will give you a strong foundation in clinical data, which will be essential for understanding the course's content and assignments.
Browse courses on
Clinical Data
Show steps
-
Read up on clinical data standards and regulations
-
Explore the different types of clinical data sources
-
Identify the challenges and opportunities of working with clinical data
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Complete beginner-friendly R tutorials
Show steps
Build your R programming skills by following guided tutorials designed for beginners, which will enhance your ability to work with clinical data in R.
Browse courses on
R Programming
Show steps
-
Find beginner-friendly R tutorials online or on platforms like Coursera
-
Follow the tutorials step-by-step
-
Practice writing basic R code
Review basic SQL skills
Show steps
This activity will help you prepare your foundational knowledge in SQL, which will be essential for the course's data manipulation assignments and projects.
Browse courses on
SQL
Show steps
-
Read through the official SQL tutorial
-
Complete the SQL practice exercises
-
Create a simple database and practice querying it
Learn the basics of R and the tidyverse
Show steps
This activity will help you develop the programming skills necessary to complete the course's data analysis assignments and projects.
Browse courses on
R
Show steps
-
Follow the official R and tidyverse tutorials
-
Complete the practice exercises provided in the tutorials
-
Install R and the tidyverse packages on your computer
Solve SQL practice exercises
Show steps
Reinforce your SQL skills by solving practice exercises, which will improve your proficiency in data querying and manipulation.
Browse courses on
SQL
Show steps
-
Find SQL practice exercises online or in textbooks
-
Solve the exercises independently
-
Review your solutions and identify areas for improvement
Complete SQL challenges and exercises
Show steps
This activity will help you develop your SQL skills and prepare you for the course's data manipulation assignments.
Browse courses on
SQL
Show steps
-
Sign up for an online SQL practice platform
-
Complete the practice challenges and exercises
-
Identify areas where you need additional practice and focus on them
Practice SQL Queries
Show steps
Reinforce your understanding of SQL and get comfortable with the syntax by practicing writing and executing queries.
Show steps
-
Review the SQL syntax and concepts covered in the course materials.
-
Use the online SQL fiddle or a local database to practice writing queries.
-
Start with simple queries and gradually increase the complexity.
Participate in online discussion forums
Show steps
Engage with peers by participating in online discussion forums, which will allow you to exchange ideas, ask questions, and learn from others' perspectives on clinical data science.
Show steps
-
Join online discussion forums related to clinical data science
-
Participate in discussions by posting questions, sharing insights, and responding to others
Create a data dictionary for the clinical data set
Show steps
This activity will help you understand the structure and content of the clinical data set used in the course.
Show steps
-
Load the clinical data set into a spreadsheet or database
-
Identify the different variables and their data types
-
Create a table or document that describes each variable, including its name, description, and possible values
Develop a data visualization project
Show steps
Apply your understanding of clinical data by creating a data visualization project, which will enhance your ability to communicate and present clinical insights effectively.
Browse courses on
Data Visualization
Show steps
-
Identify a clinical dataset
-
Choose appropriate data visualization techniques
-
Create a data visualization using a tool like Tableau or Power BI
-
Present your visualization and explain your insights
Participate in a study group with other students
Show steps
This activity will allow you to connect with other students, discuss the course material, and learn from each other's perspectives.
Show steps
-
Find other students who are taking the course
-
Set up a regular meeting time and place
-
Discuss the course material, work on assignments together, and share resources
Participate in a data science competition using clinical data
Show steps
This activity will challenge you to apply your data science skills to a real-world problem.
Show steps
-
Find a data science competition that uses clinical data
-
Develop a model or approach to solve the problem
-
Submit your solution to the competition
Find a mentor who works in the field of clinical data science
Show steps
This activity will provide you with guidance and support from an experienced professional.
Show steps
Show steps
Show steps
- Network with people in your field
- Attend industry events
- Reach out to potential mentors and ask for their guidance
Review SQL basics
Show steps
Refresh your knowledge of SQL before starting the course to strengthen your foundational understanding of data querying.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Review SQL syntax and commands
- Practice writing basic SQL queries
- Complete online tutorials or exercises on SQL
Review concepts of clinical data
Show steps
This activity will give you a strong foundation in clinical data, which will be essential for understanding the course's content and assignments.
Browse courses on
Clinical Data
Show steps
Show steps
Show steps
- Read up on clinical data standards and regulations
- Explore the different types of clinical data sources
- Identify the challenges and opportunities of working with clinical data
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Complete beginner-friendly R tutorials
Show steps
Build your R programming skills by following guided tutorials designed for beginners, which will enhance your ability to work with clinical data in R.
Browse courses on
R Programming
Show steps
Show steps
Show steps
- Find beginner-friendly R tutorials online or on platforms like Coursera
- Follow the tutorials step-by-step
- Practice writing basic R code
Review basic SQL skills
Show steps
This activity will help you prepare your foundational knowledge in SQL, which will be essential for the course's data manipulation assignments and projects.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Read through the official SQL tutorial
- Complete the SQL practice exercises
- Create a simple database and practice querying it
Learn the basics of R and the tidyverse
Show steps
This activity will help you develop the programming skills necessary to complete the course's data analysis assignments and projects.
Browse courses on
R
Show steps
Show steps
Show steps
- Follow the official R and tidyverse tutorials
- Complete the practice exercises provided in the tutorials
- Install R and the tidyverse packages on your computer
Solve SQL practice exercises
Show steps
Reinforce your SQL skills by solving practice exercises, which will improve your proficiency in data querying and manipulation.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Find SQL practice exercises online or in textbooks
- Solve the exercises independently
- Review your solutions and identify areas for improvement
Complete SQL challenges and exercises
Show steps
This activity will help you develop your SQL skills and prepare you for the course's data manipulation assignments.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Sign up for an online SQL practice platform
- Complete the practice challenges and exercises
- Identify areas where you need additional practice and focus on them
Practice SQL Queries
Show steps
Reinforce your understanding of SQL and get comfortable with the syntax by practicing writing and executing queries.
Show steps
Show steps
Show steps
- Review the SQL syntax and concepts covered in the course materials.
- Use the online SQL fiddle or a local database to practice writing queries.
- Start with simple queries and gradually increase the complexity.
Participate in online discussion forums
Show steps
Engage with peers by participating in online discussion forums, which will allow you to exchange ideas, ask questions, and learn from others' perspectives on clinical data science.
Show steps
Show steps
Show steps
- Join online discussion forums related to clinical data science
- Participate in discussions by posting questions, sharing insights, and responding to others
Create a data dictionary for the clinical data set
Show steps
This activity will help you understand the structure and content of the clinical data set used in the course.
Show steps
Show steps
Show steps
- Load the clinical data set into a spreadsheet or database
- Identify the different variables and their data types
- Create a table or document that describes each variable, including its name, description, and possible values
Develop a data visualization project
Show steps
Apply your understanding of clinical data by creating a data visualization project, which will enhance your ability to communicate and present clinical insights effectively.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Identify a clinical dataset
- Choose appropriate data visualization techniques
- Create a data visualization using a tool like Tableau or Power BI
- Present your visualization and explain your insights
Participate in a study group with other students
Show steps
This activity will allow you to connect with other students, discuss the course material, and learn from each other's perspectives.
Show steps
Show steps
Show steps
- Find other students who are taking the course
- Set up a regular meeting time and place
- Discuss the course material, work on assignments together, and share resources
Participate in a data science competition using clinical data
Show steps
This activity will challenge you to apply your data science skills to a real-world problem.
Show steps
Show steps
Show steps
- Find a data science competition that uses clinical data
- Develop a model or approach to solve the problem
- Submit your solution to the competition
Career center
Learners who complete Introduction to Clinical Data Science will develop knowledge and skills
that may be useful to these careers:
Clinical Research Associate
Clinical Research Associate
Clinical Research Associates work with doctors and patients to conduct clinical trials. They collect data from patients and monitor their progress. This course can help you develop the skills you need to become a Clinical Research Associate. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Clinical Data Analyst
Clinical Data Analyst
Clinical Data Analysts use data to improve the quality of healthcare. They collect, clean, and analyze data from clinical trials and other sources to identify trends and patterns. This course can help you develop the skills you need to become a Clinical Data Analyst. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Medical Writer
Medical Writer
Medical Writers write articles, reports, and other materials for healthcare professionals and patients. They explain complex medical information in a clear and concise way. This course can help you develop the skills you need to become a Medical Writer. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Healthcare Consultant
Healthcare Consultant
Healthcare Consultants help healthcare organizations improve their performance. They analyze data to identify areas for improvement, and then develop and implement solutions. This course can help you develop the skills you need to become a Healthcare Consultant. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. They work with Data Scientists to develop models that can predict future events. This course can help you develop the skills you need to become a Machine Learning Engineer. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Health Information Manager
Health Information Manager
Health Information Managers oversee the management of health information. They ensure that data is accurate, complete, and secure. This course can help you develop the skills you need to become a Health Information Manager. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Medical Librarian
Medical Librarian
Medical Librarians help people find and use health information. They work in libraries, hospitals, and other healthcare settings. This course can help you develop the skills you need to become a Medical Librarian. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Data Scientist
Data Scientist
Data Scientists use data to build models that can predict future events. They use a variety of statistical and machine learning techniques to develop these models. This course can help you develop the skills you need to become a Data Scientist. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Data Analyst
Data Analyst
Data Analysts use data to solve problems and make decisions. They collect, clean, and analyze data, and then present their findings to stakeholders. This course can help you develop the skills you need to become a Data Analyst. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Database Administrator
Database Administrator
Database Administrators are responsible for the design, implementation, and maintenance of databases. They ensure that data is stored securely and efficiently, and that users can access the data they need. This course can help you develop the skills you need to become a Database Administrator. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Physician
Physician
Physicians provide medical care to patients. They diagnose and treat diseases, and they prescribe medications. This course may be useful for Physicians who want to learn more about clinical data science. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Health Policy Analyst
Health Policy Analyst
Health Policy Analysts analyze and develop policies that affect the healthcare system. They work with government agencies, healthcare organizations, and other stakeholders to ensure that the healthcare system is fair, efficient, and effective. This course may be useful for Health Policy Analysts who want to learn more about clinical data science. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Nurse
Nurse
Nurses provide medical care to patients under the direction of a Physician. They administer medications, monitor patients' vital signs, and provide emotional support. This course may be useful for Nurses who want to learn more about clinical data science. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Healthcare Administrator
Healthcare Administrator
Healthcare Administrators oversee the management of healthcare organizations. They set policies, manage budgets, and ensure that the organization is running smoothly. This course may be useful for Healthcare Administrators who want to learn more about clinical data science. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
Pharmacist
Pharmacist
Pharmacists dispense medications and provide information about their use. They also work with Physicians to develop and manage medication plans for patients. This course may be useful for Pharmacists who want to learn more about clinical data science. You will learn how to use SQL to query databases, and how to use the tidyverse to analyze and visualize data. You will also learn about the ethical and legal restrictions on clinical data.
For more career information including salaries, visit:
OpenCourser.com/course/0u98hb/introduction
Reading list
We've selected 14 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Clinical Data Science.
Provides a practical guide to healthcare data analytics, including data management, data analysis, and data visualization. It also covers the use of machine learning and artificial intelligence in healthcare.
Provides a practical guide to using R for data science. It valuable resource for anyone who wants to learn more about how to use R to analyze data.
Save
Provides a practical guide to using R for text analysis. It valuable resource for anyone who wants to learn more about how to use R to analyze text data.
Save
Provides a comprehensive overview of clinical data analytics for patient safety and quality improvement. It covers topics such as data collection, data analysis, and data visualization. It also discusses the ethical and legal considerations of using clinical data analytics.
Provides a practical guide to using data science in a business setting. It valuable resource for anyone who wants to learn more about how data science can be used to improve business outcomes.
Discusses the challenges that large organizations face when they try to innovate. It provides a framework for understanding how to innovate successfully. It valuable read for anyone interested in innovation in healthcare.
Save
Provides a thought-provoking look at the ethical and social implications of data science. It valuable read for anyone who wants to learn more about the potential dangers of data science.
Provides a practical guide to using lean principles to build successful businesses. It valuable read for anyone interested in starting a business in healthcare.
Provides a unique perspective on building successful businesses. It valuable read for anyone interested in starting a business in healthcare.
Provides a realistic look at the challenges of building a successful business. It valuable read for anyone interested in starting a business in healthcare.
Save
Provides a framework for understanding how companies can achieve sustained success. It valuable read for anyone interested in building a successful business in healthcare.
Provides a practical guide to building a successful small business. It valuable read for anyone interested in starting a business in healthcare.
Save
Provides a controversial perspective on how to achieve financial freedom. It valuable read for anyone interested in starting a business in healthcare.
Save
Provides a unique perspective on how to achieve financial freedom. It valuable read for anyone interested in starting a business in healthcare.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0u98hb/introduction
Share
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Clinical Data Models and Data Quality Assessments
Effort
4 weeks of study, 1-3 hours/week
Level
Intermediate
Via
Coursera
Institution
University of Colorado System
Instructor
Laura K. Wiley, PhD
Language
English
Transcripts
Español
Français
Português
Deutsch
Italiano
中文
العربية
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日本語
हिंदी
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This course belongs to a
collection
called
Clinical Data Science. It's comprised of six courses:
- Introduction to Clinical Data Science (viewing)
- Clinical Natural Language Processing
- Clinical Data Models and Data Quality Assessments
- Predictive Modeling and Transforming Clinical Practice
- Identifying Patient Populations
- Advanced Clinical Data Science
Good to know
Prepares learners to complete other courses in the Clinical Data Science Specialization
Assists learners who have little to no programming experience
Introduces SQL and R programming skills, which are essential for data science
Provides access to an actual clinical data set and a free, online computational environment for data science
Taught by an experienced instructor with a PhD in Clinical Psychology
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