Biomedical Data Analytics

Course Overview

This course is offered through the Health Informatics area of CyberClinic Academy.

Prerequisites

• Basic statistics or quantitative reasoning is recommended.
• Basic computer literacy.
• No prior biomedical data analytics experience is required.

Learning Objectives

The course is designed to develop the following capabilities:

• Explain the role of data analytics in biomedical research and healthcare decision-making.
• Identify common biomedical and clinical data types and their analytical challenges.
• Prepare, clean, and organize biomedical datasets for analysis.
• Apply exploratory data analysis and descriptive statistical techniques.
• Create clear visualizations for biomedical and healthcare data.
• Interpret analytical findings while recognizing limitations, bias, and uncertainty.
• Apply responsible data practices involving privacy, security, reproducibility, and ethical use.

Expected Learning Outcomes

• Identify appropriate analytical approaches for common biomedical datasets.
• Prepare a biomedical dataset for analysis.
• Perform introductory descriptive and exploratory analyses.
• Create and interpret biomedical data visualizations.
• Communicate analytical findings to technical and healthcare audiences.
• Recognize common sources of bias, missingness, and data-quality problems.

Assessment & Project Work

This course includes structured assessments and applied work. Detailed instructions and submissions are available only within the authenticated learner experience.