Learners will demonstrate proficiency in business communication by effectively applying strategies and techniques to convey information in professional settings. They will exhibit competency in utilizing digital tools for communication, develop strong interpersonal skills through practical, real-world exercises, and show collaborative competence by actively contributing to group projects and teamwork.

Understanding the data-driven programming methodology and having a sound programming background are foundational skills for anyone interested in working with data. This course introduces students to the principles of programming and application design. In addition, students begin to apply the concepts of data structures and algorithms to develop data-driven software applications.

Learners will demonstrate proficiency in foundational data tools (such as Microsoft Excel) by effectively navigating, consolidating, and analyzing data across multiple worksheets. They will exhibit competency in creating macros for efficient data analysis, managing complex nested formulas for scenario planning, and designing professional corporate dashboards tailored to business needs.

Designing health research projects requires effective data analysis. This requires the integration of both healthcare and data understanding. Learners utilize information about healthcare processes, workflows, strategies and their data needs. Learners then apply this knowledge to real-world scenarios to identify and define research goals and design appropriate data projects.

This course is specifically focused towards supporting the mathematical principles required to apply the concepts of data analysis and big data analytics. Learners apply concepts such as probability, distributions, regression, topological analysis, and descriptive and inferential statistics to data-related contexts.

This course focuses on the process of initiating and executing a healthcare improvement initiative from conception to hypothesis, execution, feedback, and subsequent improvements. Learners will undergo an authentic assessment to determine the change management processes involved in delivering these improvements.

Ethical data management involves ensuring that data is collected, stored, processed, and analyzed responsibly and ethically (including privacy regulations, data protection laws, ethical guidelines, and individuals' privacy and rights).

Learners locate and select relevant, high-quality data that meets the requirements and constraints of a project. Learners then extract data from different sources (a database, a website) using the appropriate techniques(SQL, web-scraping, and Application Programming Interface (API)). Once data has been collected, it must be prepared - reviewed, cleaned, structured, and enriched - prior to analysis. The result of data preparation is a finalized dataset that is well documented and ready for analysis.

This course enables learners to develop competencies in analyzing the relationship between thinking, human behaviour, and organizational effectiveness. Learners will demonstrate the ability to critically evaluate their own behaviour and its impact on their professional and personal environments. Through applied learning, learners will acquire the skills to transform self-awareness, interpersonal relationships, and workplace dynamics using principles of human behaviour.

In this course learners use Structured Query Language (SQL) on commercial relational databases. Using SQL and SQL procedural language, learners create and manage a relational database, addressing data integrity and security. In addition, learners explore the relationship between database administration and software development.
Prerequisite: DATA1201

The first step in exploratory data analysis (EDA) is pattern identification. To identify patterns within the data, learners utilize descriptive statistical methodology that is relevant and meaningful to the project goals. Learners use graphical analysis to explore relationships and correlations within the dataset. A variety of methods are used to handle missing data and outliers within the dataset. To categorize the data, learners build unsupervised learning models. Learners summarize the outcomes of their analysis from unsupervised learning models and use the outcomes to develop actionable business insights and recommend further analysis.

This course provides learners with the knowledge and skills necessary to manage healthcare data effectively by ensuring quality, accuracy, and accessibility of health information for patient care, administrative decision-making, and research purposes.

Learners will utilize evidence-based practices to improve clinical and administrative decision-making in healthcare. Learners will evaluate and apply current research evidence to inform healthcare decisions, optimize patient care, and enhance healthcare processes.

Using identified relationships within the data, learners build simple predictive models based on regression and classification. Learners fit the data to the model, assess the model's performance, and make adjustments to the model's parameters to develop actionable business insights. Then they integrate their technical and communication skills to build and refine simple and complex visualizations to optimize effectiveness. Finally, learners close off a project, ensuring that key stakeholders have what they need to make decisions.

This course provides learners with a comprehensive understanding of health informatics, including the use of information technology to enhance healthcare delivery, patient outcomes, and the overall healthcare system. Learners will learn and apply data informatics principles in a clinical setting.

This course examines the principles and techniques involved in monitoring and enhancing healthcare quality, safety, and performance. Learners will apply this knowledge to generate healthcare metrics to support continuous improvement.

Working alone or in a small team, students research, design, develop, and implement an applied big data analytics research project to satisfy a real healthcare organizational or community need. Students are expected to apply all of their knowledge and skills to produce a functioning prototype of their project idea.