M.Eng. in Applied Artificial Intelligence

Program Overview

The M.Eng. in Applied Artificial Intelligence is a 30-credit degree program, typically completed within 1.5 to 2 years for full-time students. The curriculum is designed to provide a comprehensive understanding of AI fundamentals and their engineering applications. Students are required to complete one mathematical foundation course (3 credits), four core courses in AI (12 credits), three concentration courses in a chosen specialization (9 credits), and two elective courses (6 credits). This structured yet flexible approach allows students to tailor their studies to specific areas of interest within AI applications. Stevens also offers a dual M.S./M.Eng.-MBA degree for those seeking a blend of deep technical AI knowledge and strong management skills. The program is available both on-campus and fully online through StevensOnline, offering significant flexibility. Stevens reports impressive career outcomes for its Applied AI graduates, with 100% employed within three months of graduation and a strong mean compensation of $90,000 for the Class of 2023.

STEM-designated: Yes, the Stevens Institute of Technology M.Eng. in Applied Artificial Intelligence program is unequivocally STEM-designated. This is a crucial advantage, particularly for international students. The STEM designation makes them eligible for a 24-month extension of their Optional Practical Training (OPT) in the United States, allowing for a total of up to three years of valuable post-graduation work experience. This designation clearly reflects the program's rigorous quantitative, scientific, and technological focus, which is highly valued by employers in the rapidly expanding fields of artificial intelligence, machine learning, and data science.

Curriculum: The 30-credit curriculum provides a robust foundation in AI theory and its application to engineering challenges. The mathematical foundation course ensures students have the necessary quantitative background. Core courses typically include "Applied Machine Learning," "Pattern Recognition and Classification," "Data Acquisition, Modeling and Analysis: Big Data Analytics," and "Data Acquisition, Modeling and Analysis: Deep Learning." Beyond the core, students choose from various concentrations that bridge AI with specific engineering disciplines, such as Computer Engineering, Electrical Engineering, Software Engineering, Data Engineering, Biomedical Engineering, Mechanical Engineering, Systems Biology, and Artificial Intelligence in Design and Construction. Elective courses further deepen specialization, covering topics like Applied Game Theory and Evolutionary Algorithms, Digital Signal Processing, Introduction to Control Theory, and various programming courses (e.g., Python, Java, C++). The curriculum emphasizes hands-on learning, project work, and the development of both software and hardware skills applicable across multiple engineering domains.

Research Focus: The M.Eng. in Applied Artificial Intelligence program at Stevens has a strong applied research focus, integrating with the broader research initiatives of the Stevens Institute for Artificial Intelligence (SIAI). SIAI is an interdisciplinary collaboration involving over 100 faculty members from across engineering, business, systems, and design, dedicated to solving pressing global problems through AI and machine learning. Research efforts are concentrated on advancing the fundamentals and applications of AI and machine learning to address real-world challenges in areas such as intelligent communication networks, autonomous robotics, image processing and computer vision, smart health, biomedical engineering, financial engineering, transportation engineering, embedded systems, and information systems security. While the M.Eng. is primarily a professional degree, students benefit from exposure to cutting-edge research through their coursework and faculty expertise, and opportunities for research projects exist for interested students.

Industry Engagement: Stevens Institute of Technology places a very high priority on industry engagement for its Applied Artificial Intelligence program. Its strategic location in the New York metropolitan area provides unparalleled access to a vast network of leading technology companies, financial institutions, healthcare providers, and engineering firms that are at the forefront of AI adoption. The curriculum is continuously updated to integrate rapidly evolving technologies, including generative AI, and to meet the latest labor market demands. Faculty members often have extensive industry experience, bringing invaluable practical insights and connections into the classroom. Stevens' strong alumni network and robust Career Center facilitate extensive networking opportunities, internships, and co-op experiences, ensuring graduates are well-prepared for roles in AI development, machine learning engineering, data science, and R&D across diverse sectors. The program actively prepares students for a rapidly evolving technological and professional landscape.

Global Perspective: Stevens Institute of Technology fosters a strong global perspective within its M.Eng. in Applied Artificial Intelligence program. This is cultivated through its diverse international student body, which enriches classroom discussions with varied insights into international AI development practices, global ethical considerations in AI, and cross-cultural applications of AI technologies. The nature of artificial intelligence and its potential impact on industries and societies is inherently global, with applications spanning smart cities, global supply chains, and international healthcare initiatives. The program prepares graduates to contribute to international AI collaborations, understand global standards and regulations, and navigate the complexities of working in a globally connected industry. This global outlook, combined with Stevens' rigorous technical education and emphasis on practical, application-oriented learning, ensures graduates are well-equipped for impactful careers in the worldwide AI landscape.