Course Overview
This course provides healthcare professionals with a foundational understanding of artificial intelligence (AI) and its applications in the healthcare industry. Participants will explore the basic principles of AI and machine learning (ML), focusing on how these technologies can enhance patient care, streamline healthcare operations, and support clinical decision-making. Key concepts covered include an introduction to AI and ML, the ethical and regulatory considerations of implementing AI in clinical settings, and the role of data in AI-driven healthcare solutions. Students will learn to manage healthcare data, understand basic big data analytics, and explore how AI can be integrated into clinical decision support systems (CDSS). The course also introduces the practical steps for planning and managing AI implementation projects, with a focus on collaboration, training, and evaluation of AI performance. By the end of this course, participants will be able to identify the opportunities and challenges associated with AI in healthcare, understand its potential to improve patient outcomes, and recognize the critical role of data management and ethical considerations in deploying AI technologies effectively. This course is ideal for clinicians and healthcare professionals interested in gaining foundational knowledge of AI and its evolving role in modern healthcare.
Prerequisite(s)
- No prerequisites are required for this course.
Credits
3.0
Domestic fees
$963.23
International fees are typically 3.25 times the domestic tuition. Exact cost will be calculated upon completion of registration.
Learning Outcomes
Upon successful completion of this course, the student will be able to:
- Understand AI Fundamentals: Explain the basic principles of artificial intelligence and machine learning, and describe their applications within the healthcare sector.
- Navigate Ethical and Regulatory Issues: Identify and discuss the ethical, legal, and regulatory considerations associated with the implementation of AI technologies in healthcare settings.
- Optimize Healthcare Data Management: Demonstrate proficiency in collecting, storing, and preprocessing healthcare data, ensuring adherence to privacy and security standards.
- Leverage Health Data Analytics: Utilize health data analytics techniques to extract meaningful insights from healthcare datasets and inform clinical and operational decision-making.
- Integrate AI into Clinical Decision Support Systems: Explain how AI can be integrated into clinical decision support systems (CDSS) to assist healthcare professionals in making informed clinical decisions.
- Understand AI Implementation Processes: Identify key steps in planning and managing the introduction of AI technologies into healthcare settings, including considerations for team collaboration, training, and monitoring AI performance
- Assess AI Applications: Describe methods for evaluating the performance and impact of AI applications in healthcare, ensuring they meet essential clinical and operational requirements while contributing to continuous improvement.
Effective as of Fall 2025
Related Programs
Artificial Intelligence in Healthcare (DIGH 7600) is offered as a part of the following programs:
- Indicates programs accepting international students.
School of Health Sciences
- Digital Health
Advanced Certificate Part-time
Course Offerings
Spring/Summer 2026
Below is one offering of DIGH 7600 for the Spring/Summer 2026 term.
CRN 70366
Dates
Apr 20 - Jun 26 Loading
- CRN 70366
- $963.23 Domestic fees
Class meeting times
Duration
10 weeks
Instructor
Daniel Anvari
Course outline
Important information
- Important course information will be sent to you prior to your course start date. Check your myBCIT email account to access this information.
- Online classes are held weekly on Wednesdays from 6:00 PM to 8:00 PM Pacific time.
Confirmation
Required
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Status
If you have any questions about this course, please contact us.
Programs and courses are subject to change without notice. Find out more about BCIT course cancellations.