Biomedical Engineering Graduate Certificates

This course covers the basic principles of artificial intelligence (AI) and its biological and medical applications. With recent progress in digitized data acquisition, machine learning, and computing infrastructure, AI is increasingly used in various fields of life. New breakthroughs and technologies are emerging from technology companies and research institutes at a rapid pace. Medicine is identified as one of the most promising application areas, and AI is changing the landscape of healthcare and biomedical research. This course will provide the basic principles of AI technologies, outline recent breakthroughs and their applications, and identify the challenges for further progress in medical AI systems. The course will also be featured by invited guest speakers who have real-world AI application experiences. All students should have extensive experience in computer programming and be familiar with Python programming.

Machine learning is an increasingly important tool for understanding datasets in Biomedical Engineering. The machine learning models introduced will include linear and logistic regression, classification using Naïve Bayes, Decision Trees, Support Vector Machines, and clustering. This course will use the python programming language, and requires basic programming skills not necessarily in python. Students choose a dataset for the final project which may come from their research.

This project-based course will teach systems analysis and data science techniques using digital health data. The project will have students: collect data on themselves throughout the semester using a provided Ōura Ring wearable device (at no cost to the student); build a secure system to store, access, and analyze the data; and use signal processing and machine learning approaches to identify and analyze trends in collected signals. Lectures will cover a variety of topics, including systems analysis, data science, and digital health. No prior knowledge of biology or human health is required. Prerequisites: Signals and Systems (BMEN 3302 or EE 3302 or equivalent), Statistics (ENGR 3341 or equivalent).

Introduction to Medical Device Product Development (3 semester credit hours) This course introduces students to the process of taking an engineering solution to a medical need from a concept to the marketplace. This course will examine topics, analysis tool and techniques pertinent to designing medical devices, or participating as a member of a design team. Engineering functions related to design, such as regulatory affairs, quality systems management, formal product testing, and user validation will also be discussed. Students will gain practical experience using the concepts taught through class projects modeled on actual medical devices.

Good Manufacturing Practices (3 semester credit hours) This course introduces students to the regulatory requirements and best practices for medical device good manufacturing practices. A wide range of engineering topics are taught that will expose students to the core concepts and deliverables in manufacturing engineering. Students will gain practical experience through the application of learned concepts in class projects and assignments related to engineering design and its manufacturing process development, planning, control, and improvement. Students will understand the influence of manufacturing throughout the regulated product lifecycle and learn to think critically and holistically when determining how to establish medical device manufacturing processes. Department consent required.

Six Sigma Yellow Belt for Biomedical Engineers (3 semester credit hours) The goal of this course is to prepare bioengineers in the techniques and methodologies related to Six Sigma. While Six Sigma generally aims to improve process performance and reduce variation via a systematic framework, the concepts and tools taught in this class extend into product design and are a valuable asset to quality assurance. Disclaimer: Although students will not receive the Six Sigma Yellow Belt certification from taking this course alone and this course is not associated with the American Society for Quality (ASQ), students will learn each Body of Knowledge needed to prepare for the certification examination using the recommended ASQ textbook.

Special Topics in Biomedical Engineering (1-9 semester credit hours) May be repeated for credit. Department consent required.