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Foundations of Healthcare Data Analytics
Course
Foundations of Healthcare Data Analytics
Build a strong foundation in healthcare data analytics, including clinical data, standards, privacy, and practical skills for responsible analysis.
Flexible Schedule
Intermediate Level
Mentor Support
Estimated Time
4 weeks
2-3 hours/week
2-3 hours/week
Healthcare generates vast amounts of data every day from electronic health records and lab systems to imaging, devices, and claims. If youre looking to build analytics skills for healthcare, or eager to understand and work with healthcare data more effectively, this course is for you.
In this course, youll explore the foundational landscape of healthcare data and understand what makes it distinct from other domains. Youll learn how data flows through clinical and administrative systems, the formats and standards that shape it, and the challenges posed by fragmentation, interoperability issues, and data quality concerns.
Youll discover why privacy, security, and regulatory frameworks like HIPAA and GDPR are essential when handling patient information. Youll also work through the core steps of the healthcare data analytics workflow, including identifying data sources, cleaning and validating datasets, exploring patterns, and preparing data for downstream analytical tasks.
The key features of this course include hands-on labs using real-world healthcare datasets and interactive exercises that simulate common analytics scenarios.
By the end of the course, youll have the foundational skills needed to interpret, prepare, and analyze healthcare data responsibly and effectively.
This course comprises four purposely designed modules that take you on a carefully defined learning path.
It is a self-paced course, which means it is not run to a fixed schedule with regard to completing modules or submitting assignments. To give you an idea of how long the course takes to complete, it is anticipated that if you work 2-3 hours per week, you will complete the course in 4 weeks. However, as long as the course is completed before the end date, you can work at your own pace.
The materials for each module will become available when you start the particular module. Methods of learning and assessment will include videos, reading material, online exams questions, and a final peer review assignment.
Once you have successfully completed the course, you will earn your Certificate of Completion.
By the end of this course, you will be able to:
- Perform data analysis and interpret results.
- Integrate data from multiple sources.
- Understand and apply data literacy skills.
- Preprocess and clean datasets.
- Work with database systems.
- Use descriptive analytics to summarize data.
- Understand healthcare procedures and regulations.
- Apply health informatics concepts.
- Ensure HIPAA compliance for data privacy.
- Work with relational databases.
- Use spreadsheet software for data tasks.
- Apply statistical programming techniques.
Professionals in healthcare, public health, IT, or data roles
Basic Python programming skills required
Course Outline
Video: Specialization Overview (4:35)
Video: Course Introduction (2:53)
Reading: Course Overview
Reading: Course Learning Objectives and Syllabus
Reading: Grading Scheme
Video: Meet Your Instructor (6:12)
Reading: How to Make the Most of This Course
Reading: Module Introduction and Learning Objectives
Activity: Exploring Healthcare Data in Action
Video: Where Healthcare Data Comes From (5:21)
Video: Comparing Healthcare Data Sources (5:14)
Reading: Case Scenario: How Data Helps Reduce Hospital Readmissions
Lab: Exploring Patient Visit Data in Excel
Practice Quiz: Understanding Healthcare Data Sources
Reading: A Day in the Life of Healthcare Data
Video: Overview of Healthcare Coding and Data Standards (5:43)
Lab: Exploring Healthcare Standards with Sample Data Sets
Reading: Reflecting on Healthcare Data Structures, Standards, and Coding Practices
Practice Quiz: Healthcare Data Structures and Standards
Video: Understanding Healthcare Data Flow from Collection to Analysis (5:15)
Video: Integration Technologies and Interoperability in Healthcare Systems (5:59)
Practice Quiz: Healthcare Data Flow and Integration
Reading: Module Summary: Foundations of Healthcare Data
Graded Quiz: Foundations of Healthcare Data
Reading: Module Introduction and Learning Objectives
Video: The Importance of Patient Data Privacy in Healthcare Analytics (3:41)
Video: Core Security Principles: Confidentiality, Integrity, and Availability (5:04)
Reading: Notable Healthcare Data Breaches
Practice Quiz: Understanding Patient Data Privacy and Security
Video: Understanding HIPAA and Global Data Protection Frameworks (5:04)
Video: Patient Rights, Data Consent, and Compliance in Practice
Activity: Applying Data Protection and Patient Consent Principles in Healthcare
Practice Quiz: Healthcare Data Protection Laws and Regulations
Video: Data Protection Techniques (5:27)
Video: Implementing Secure Access and Compliance in Healthcare Systems (4:46)
Activity: Data Protection in Practice
Practice Quiz: Best Practices for Secure Data Handling and Compliance
Reading: Module Summary: Data Privacy and Security in Healthcare
Graded Quiz: Data Privacy and Security in Healthcare
Reading: Module Introduction and Learning Objectives
Video: Healthcare Data Collection Methods (4:15)
Reading: Overcoming Healthcare Data Collection Challenges
Video: Importing and Preparing Healthcare Data (4:32)
Lab: Importing and Consolidating Multi-Source Healthcare Data
Practice Quiz: Collecting and Importing Healthcare Data from Multiple Sources
Video: Fundamentals of Relational Databases in Healthcare (5:04)
Video: Managing and Querying Healthcare Databases with SQL
Lab: Building and Querying a Relational Healthcare Database Using SQL
Practice Quiz: Organizing Healthcare Data Using Relational Databases
Video: Identifying and Cleaning Data Quality Issues
Video: Maintaining Data Consistency and Validation Across Systems
Reading: Data Quality Metrics and Standards in Healthcare Analytics
Lab: Cleaning and Validating Healthcare Data Using Python
Practice Quiz: Ensuring Data Quality and Consistency for Analysis
Reading: Module Summary: Preparing Healthcare Data for Analysis
Graded Quiz: Preparing Healthcare Data for Analysis
Reading: Module Introduction and Learning Objectives
Reading: How will you be graded?
Project: Final Project: Building Your End-to-End Healthcare Data Analytics Solution
Reading: Comparing Your Work
Video: Course Summary (3:27)
Course Glossary: Foundations of Healthcare Data Analytics
Final Exam: Foundations of Healthcare Data Analytics
Reading: Congratulations and Next Steps
Reading: Team and Acknowledgments
Why Learn with SkillUp Online?
We believe every learner is an individual and every course is an opportunity to build job-ready skills. Through our human-centered approach to learning, we will empower you to fulfil your professional and personal goals and enjoy career success.
Reskilling into tech? We’ll support you.
Upskilling for promotion? We’ll help you.
Cross-skilling for your career? We’ll guide you.
Personalized Mentoring & Support
1-on-1 mentoring, live classes, webinars, weekly feedback, peer discussion, and much more.
Practical Experience
Hands-on labs and projects tackling real-world challenges. Great for your resumé and LinkedIn profile.
Best-in-Class Course Content
Designed by the industry for the industry so you can build job-ready skills.
Job-Ready Skills Focus
Competency building and global certifications employers are actively looking for.
FAQs
No, the Foundation of Data Analytics in Healthcare course is designed for beginners. Youll start with the basics of healthcare data and gradually understand how to work with it. Coding is not required, and concepts are explained in a simple, practical way.
Youll learn how healthcare data is collected, structured, and used across systems like hospitals and clinics. The course also covers data sorting, interpretation, and basic analysis to support real-world healthcare decisions.
No, This healthcare data analytics course is highly relevant for healthcare professionals like nurses, administrators, or allied health workers. But someone from a non-healthcare background can also benefit from this course. It helps you understand the data behind patient care, making your role more informed and impactful in modern healthcare systems.
Yes, the Foundations of Healthcare Data Analytics course includes hands-on exercises using real or simulated healthcare datasets. This helps you understand practical challenges like data quality, fragmentation, and how insights are generated in real scenarios.
You can explore roles like healthcare data analyst, clinical data coordinator, or health informatics specialist. These roles involve working with patient data, improving systems, and supporting data-driven decisions in healthcare organizations.
Healthcare data handling is more sensitive, complex, and regulated. It includes patient records, clinical data, and administrative information and must follow strict privacy laws like HIPAA compliance, making accuracy and security extremely important.
This beginner-level course is designed to help you understand core concepts, workflows, and tools in a structured and manageable way. You can build a strong base within a few weeks if you stay consistent.
In order to gain access to lectures and assignments, you need to pay for the course and complete the required assessment. And to get the certificate, you need to complete the entire modules within the Foundations of Healthcare Data Analytics course.
Yes, recordings of each class will be uploaded into the Learning Management System (LMS). Hence, you will be able to check out the recordings on the LMS platform in case you miss any class.
This data analytics course is ideal for healthcare professionals, graduates, or beginners who want to understand how data is used in healthcare. If youre curious about patient data, hospital systems, or want to explore data analytics without a technical background, this is a practical starting point.
Type of certificate
Certificate of Completion
About this course
04 Modules
12 Skills
Includes
Discussion Space
20 Videos
05 Hands-on labs
08 Practice quizzes
03 Graded quizzes
01 Project
01 Final exam
Exercises to explore
Jupyter Notebook
Google Colab
This course has been created by
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