Online Course – Certified Professional Internship in Health and Medical Informatics for Google Data Analytics, University of California, Davis

Upgrade your healthcare data science career. Transfer your data analytics skills to the complex world of healthcare.

Suggested by: Coursera (What is Coursera?)

Professional Certificate

Intermediate level

No prior knowledge required

Time to complete the course

7-day free trial

No unnecessary risks

Skills you will acquire in the course

  • Identifying healthcare data types
  • Understanding data sources and challenges
  • Comparing different healthcare terms
  • Performing practical data modeling tasks
  • Analyzing questions of efficiency and effectiveness in healthcare
  • Determining data types in different data sets
  • Disclosure of data sources and participants
  • Data quality and validity analysis
  • Recommending improvements in patient care

What you will learn in the course

Courses for which the course is suitable

  • Healthcare Data Analyst
  • Healthcare Data Scientist
  • Healthcare Project Manager
  • Medical data analysis software developer
  • Health data management consultant
  • Healthcare Data Quality Specialist
  • Researcher in the field of health sciences
  • Medical Information Systems Manager
  • Healthcare Systems Analyst
  • Healthcare Data Strategy Planner

Internship – 4-part course series

This internship is designed for data and technology professionals who have no prior experience in healthcare and are interested in transitioning into a field that will work with health data.

Over the course of four courses, you will identify the types of data, their sources, and the challenges associated with health data, along with methods for selecting and preparing data for analysis.

Main topics:

  • Types of health data
  • Data sources and challenges
  • Comparison of terms: administrative data, clinical data, insurance claims, patient-reported data, and external data
  • Practical data modeling tasks
  • Questions of efficiency and effectiveness in healthcare

This training will prepare you to upgrade raw health data into actionable information.

Hands-on Learning Project

Learners will examine various health data sets to:

  • Determine the data types
  • Discover the sources and participants of the data
  • Analyze data quality and validity
  • Recommend improvements in patient care

Details of the courses that make up the specialization

Health data classification

Course 1: 13 hours

Rating: 4.4 (117 ratings)

What you will learn: This course will lay the foundation for your journey into the world of healthcare data and provide you with the knowledge and skills required to work in the healthcare industry as a data scientist. We will learn about the many aspects to consider in healthcare and define the value and growing need for analysts in this field.

  • Health goals and various concepts in health data.
  • Common clinical representations of data in healthcare systems.
  • Different types of health data and their sources.
  • Integrating data and defining important concepts in the field.

Course 2: 11 hours

Rating: 4.6 (52 ratings)

What you’ll learn: This course gives you a glimpse into the importance of working in the field of healthcare data analytics. You’ll learn how data is collected from patients, moved into data warehouses, and advanced into valuable insights.

  • Overview of common data models.
  • Ensuring clear communication and data quality.
  • Opportunities in the field of health data analysis.

Course 3: 11 hours

Rating: 4.6 (100 ratings)

What you will learn: This course will provide insight into how to protect data assets and maintain their quality. You will learn why data quality is important and how healthcare professionals monitor, manage, and improve data quality.

  • Data quality maintenance and governance.
  • Measuring data quality using metadata.
  • Human and computerized systems for preserving data quality.

Course 4: 10 hours

Rating: 4.6 (27 ratings)

What you will learn: In this course, we will go over analytical solutions to routine healthcare problems. You will build various data structures and learn to extract, transform, and transport data to solve medical problems.

  • Data grouping and classification of medical codes.
  • Harmonization of data from different sources.
  • Create a data dictionary to communicate the source and value of the data.