AI-Enabled Systems Engineering Graduate Certificate

Program Description

This graduate certificate is designed to prepare students for advanced careers at the intersection of systems engineering and artificial intelligence. Grounded in academic principles and enriched by industry relevant applications, the certificate emphasizes the design, integration and evolution of complex systems within data intensive and technology driven environments. Students will build strong foundational expertise in systems architecture and engineering methodologies, alongside specialized proficiency in leveraging artificial intelligence and machine learning for enhanced decision making, process automation and intelligent system design.

The certificate includes courses on data exploration and manipulation, applied AI, AI for software engineering, and AI-enhanced special projects, equipping graduates to lead innovation across a wide range of industries.

Who Should Consider This Certificate

• Engineers and technical professionals seeking to broaden their impact beyond a single discipline and integrate AI into complex system solutions

• Graduate students looking to add a systems perspective and practical AI competencies to their academic or professional profile

• Working professionals who value flexible learning formats and want to upskill in AI-driven engineering and decision support

• Individuals interested in roles involving systems integration, engineering leadership, intelligent automation, or applied AI

• Professionals transitioning into AI-enabled roles such as AI product, systems, or solution engineering

Educational Objectives

• Develop systems-minded professionals who can navigate complexity, uncertainty and rapid technological change driven by AI

• Prepare students to contribute to and lead multidisciplinary engineering and AI initiatives

• Enhance career mobility by building transferable skills in systems thinking, data-driven reasoning and AI integration

• Complement graduate degree programs with a strong foundation in systems engineering principles and AI-enabled system design

• Foster responsible innovation by promoting awareness of governance, trustworthiness, and societal impacts of AI systems

Educational Outcomes

• Think holistically about complex systems and the interactions between technical, human, organizational and data components

• Apply systems engineering and AI methods to support effective decision-making, prediction and optimization

• Evaluate trade-offs, risks, and ethical implications of AI-enabled systems across their lifecycle

• Design and assess AI enabled software systems architectures that incorporate machine learning, data pipelines, and intelligent services

• Collaborate and communicate effectively in multidisciplinary teams spanning engineering, data science and domain experts