Program Overview

Program Overview

The Engineering and Technology Management (ETM) program at Washington State University is designed for working professionals. The program offers a Master's degree and various certificate programs, including Constraints Management, Supply Chain Management, Industrial Leadership, Project Management, Six Sigma Quality Management, and Systems Engineering Management.

Master's Degree Requirements

• A bachelor's degree from an accredited institution
• A transcript
• At least one letter of recommendation
• A personal statement
• A résumé showing work experience

Certificate Program Requirements

• A bachelor's degree from an accredited institution
• A transcript
• A personal statement
• A résumé

Course Description: E_M 596 Advanced Topics in Engineering Management II – Managing Emerging Digital Technologies

The course focuses on the critical analysis of emerging technologies such as artificial intelligence, machine learning, the Internet of Things (IoT), digital twins, robotics, and digital governance. By studying these technologies through theoretical frameworks and real-world case studies, students will develop a foundation in their applications and implications within engineering contexts.

Course Details

• Term: Spring 2026
• Duration: 16 weeks, Live Online
• Price: Non-Refundable Application Fee: US$90
• Admission: Apply online via EngineeringCAS. Priority application deadlines by term: November 15 (Spring); July 15 (Fall); March 15 (Summer)

Course Objectives

The primary objective of this course is to equip engineers with the knowledge and skills needed to harness emerging technologies effectively. By the end of the course, students will:

• Analyze the role of emerging technologies in various engineering fields and their impact on engineering processes.
• Evaluate the technical, economic, and ethical challenges associated with the adoption of these technologies. Apply risk mitigation strategies to successfully integrate these technologies into real-world projects.
• Propose innovative solutions using emerging technologies to address contemporary engineering challenges.

Learning Outcomes

Upon completion of the course, students will:

• Define and explain the fundamental concepts of Artificial Intelligence (AI) and its core components such as machine learning, neural networks, and deep learning in the context of engineering applications.
• Evaluate future trends and advancements in emerging technologies to identify potential applications and challenges for engineers in solving global problems.
• Assess the impact of automation technologies on the engineering workforce and project outcomes.
• Evaluate the ethical, technical, and operational challenges that come with implementing new technologies in engineering projects.
• Synthesize data-driven insights to improve decision-making processes when adopting new technologies in engineering projects.

Gain Expertise in

• Applying AI to optimize engineering processes
• Analyzing engineering data sets with ML techniques for improved outcomes
• Understanding regulatory compliance for AI, IoT, and blockchain technologies
• Addressing ethical challenges in the application of AI and autonomous systems
• Leveraging digital transformation to improve data-driven engineering outcomes
• Ethical considerations and compliance in technology adoption
• Data governance and the role of digital transformation in engineering

Tuition and Fees

View Tuition and Fees for Tuition Rates.

Student Type

The program is designed for working professionals and offers various options for different student types, including but not limited to:

• Graduate Student
• International Student
• Transfer Student
• Undergraduate Foundation Student

Concentrations and Certificates

The program offers concentrations and certificates in:

• Constraints Management
• Supply Chain Management
• Industrial Leadership
• Project Management
• Six Sigma Quality Management
• Systems Engineering Management

Additional Information

The ETM program values work experience and determination. Provisional admission may be offered to those who do not meet the Graduate School’s minimum 3.0 GPA requirement. The program accepts both academic and professional letters of recommendation.