The Program Educational Objectives (PEOs) are to produce graduates who can:

• Demonstrate expertise as engineering scholars through significant technical, research, and leadership accomplishments that contribute to advancing knowledge in their field.
• Participate in lifelong scholarly pursuits, including advanced research, interdisciplinary collaboration, and the dissemination of knowledge through professional and academic channels.
• Contribute to the development of local and global communities, upholding the highest standards of ethical, social, and professional responsibility in research and innovation.

The Program Learning Outcomes (PLOs) are to instill in graduates the ability to:

• Apply advanced research, critical analysis, and innovative thinking to solve highly complex problems in intelligent systems engineering using specialized and interdisciplinary knowledge in artificial intelligence, automation, and data-driven decision-making.
• Design and execute independent, original research that integrates knowledge from various fields, employing highly advanced cognitive, computational, and algorithmic skills to advance the state-of-the-art in intelligent systems.
• Communicate proficiently to present, defend, and critique complex ideas and findings in intelligent systems engineering through scholarly writing, professional presentations, and industry collaborations.
• Recognize and navigate complex ethical, social, and professional responsibilities in intelligent systems research and applications, making informed judgments that consider the global, economic, environmental, and societal impacts of AI and automation.
• Contribute effectively in multidisciplinary environments, demonstrating autonomy, leadership, and the capacity to foster team collaboration in intelligent systems research and development.
• Develop and implement computational models, design and conduct rigorous experimentation, analyze and interpret incomplete or ambiguous data, and apply advanced machine learning and artificial intelligence techniques to derive innovative and practical solutions.
• Self-assess, acquire, and integrate new advanced knowledge in intelligent systems engineering, demonstrating a critical awareness of contemporary issues, emerging challenges, and recent advancements in AI, deep learning, robotics, and smart technologies.