Master of Science in Engineering Artificial Intelligence (MS EAI) is a 16-20 month (3-4 semesters) program that opens the door to advanced skills that enable engineers to design powerful solutions to today's challenges. The MS EAI degree intersects with specific engineering disciplines but more importantly cuts across important problems in areas such as transportation, building systems, manufacturing, energy, agriculture, security, health, and climate. Students learn to combine a foundation in artificial intelligence, machine learning, and data science with their engineering, information technology, and software skills through theoretical and practical hands-on study of real-world applications.
MS EAI program objective
The MS EAI degree seeks to take AI and embed it in engineering frameworks including engineering representations, applications within engineered systems, and discipline-specific interpretations of system outcomes. Within these frameworks students will learn to invent, tune, and specialize AI algorithms and tools for engineering systems.
Possible career paths for MS EAI graduates
Upon completion of the MS EAI program, graduates possess a diverse skill set and deep understanding of information technology principles, making them well-equipped for various career opportunities in both technical and managerial roles. Below are some common career paths pursued by MS EAI graduates:
- Software developer/engineer: Design, develop, and maintain software applications and systems to meet organizational needs.
- Network architect/engineer: Design, implement, and maintain an organization's network infrastructure, ensuring reliability and security.
- Data scientist: Analyze complex datasets to extract insights and drive data-driven decision-making.
- Cybersecurity consultant: Provide expert advice and solutions to organizations to enhance their cybersecurity posture.
- Technical product manager: Bridge the gap between technical and non-technical stakeholders to deliver innovative products.
- Ph.D. candidate: Pursue further studies and research in information technology by enrolling in a Ph.D. program.
- Entrepreneurship/startup founders: Some MS EAI graduates choose to start their own businesses or tech startups, leveraging their technical expertise and entrepreneurial spirit to innovate and create new solutions in the IT industry.
MS EAI capstone
Students place applicable learning into practice through a 24-unit project. The project starts in the first semester through a seminar class where students study different engineering applications of AI and machine learning to opportunities in Africa. In subsequent semesters they develop their system design as well as their project plan. In their second year, they implement and test their solution for review by faculty and external sponsors.
Graduation requirements for the MS EAI degree
To complete the MS EAI degree, students are required to complete 144 units of coursework with a cumulative quality point average of at least 3.0 (i.e., a B grade in each course). Below is the breakdown of the required completion units:
- 72 units of core courses composed of 12 units from each of the six categories
- Mathematical Fundamentals
- Introduction to Artificial Intelligence
- Introduction to Machine Learning
- Data Analytics
- Advanced Artificial Intelligence and Machine Learning
- EAI System Designs
- 48 units of electives. Elective courses are where students gain a focus relative to their engineering discipline. 36 units must be 600 level or above the College of Engineering departments. 12 units must be at either 300 level or above from the College of Engineering departments.