0522 - Python for Health Data

Course Description

Details

Canada’s health care landscape is experiencing a profound digital evolution, reshaping how patient care, public health policy, and operational decisions are informed by data. Driven by advances in analytics, organizations are increasingly tapping into data to enhance patient outcomes, improve resource management, and ensure more equitable access to care. 

Against this backdrop, professionals need the skills to turn raw data into actionable insights. This course empowers participants to leverage Python’s versatile toolkit for extracting, cleaning, analyzing, and visualizing health-related data, preparing them to navigate the complexities of today’s information-rich health care environment. Whether working in health information management, policy analysis, clinical informatics, or broader administrative and research roles, you will gain the analytical acumen to support evidence-based decision-making and drive meaningful improvements in Canada’s health systems. 

Course Overview

• Expert instruction from University of Waterloo faculty. 
• Live discussion sessions via Zoom each week. 
• Peer discussions and networking opportunities. 
• Case studies from well-known organizations within the health care sector. 
• Four hours of independent work online each week (including graded assignments and activities). 
• Capstone project that integrates your learning. 
• Attendance requirement: It is highly recommended that participants attend live sessions, but it is not required. Live sessions will be recorded and available for all participants to view. 

Who Should Enrol

As Canada’s health sector invests in digital infrastructure and data-driven capabilities, there is a growing need for professionals who can bridge the gap between raw datasets and actionable intelligence. This program is ideal for: 

• Health information management professionals seeking to upskill in data analytics, preparing themselves for new roles that blend operational expertise with digital health competencies. 

• Public health practitioners and policy analysts wishing to leverage advanced data insights for better policymaking, intervention design, and health equity strategies. 

• Health care administrators and operations managers looking to enhance their strategic decision-making through robust data analysis and visualization. 

• IT and data specialists in health care settings hoping to broaden their skill set, enabling them to support and implement data-driven initiatives and innovations. 

• Individuals from other industries who recognize the value of data analytics in health care and want to position themselves at the forefront of Canada’s digital health transformation. 

Cultivating data literacy and technological fluency is critical for those aiming to excel and advance in tomorrow’s health care ecosystem. By developing these in-demand skills, participants will not only stay relevant in an evolving job market but also contribute to building a more responsive, effective, and patient-centered Canadian health care system. 

What You Will Learn

• Python fundamentals for health analytics: Strengthen your foundational Python skills for working with health care datasets, performing data manipulation, and streamlining analytical workflows. 
• Sourcing and integrating health data: Learn how to access, interpret, and integrate open health data from various Canadian sources and platforms. 
• Data preparation and quality assurance: Apply best practices in data cleaning and preprocessing, ensuring the integrity, reliability, and privacy considerations of health data. 
• Exploratory data analysis (EDA) in healthcare: Use Python libraries (such as Pandas, NumPy, and Matplotlib) to identify trends, detect anomalies, and uncover patterns that inform evidence-based policies and clinical strategies.
• Data storytelling and visualization: Transform complex health metrics into meaningful visuals and narratives that support informed decision-making among health care administrators, clinicians, policymakers, and public health leaders. 
• Real-world case studies: Work through practical examples that address challenges in areas like pandemic response, resource allocation, population health, and system efficiencies—all within the Canadian context.