Master's in Applied Artificial Intelligence

1 Years On Campus Masters Program

Stevens Institute of Technology

Program Overview

The Master of Science in Applied Artificial Intelligence at Stevens Institute of Technology equips students with advanced knowledge of artificial intelligence, machine learning, deep learning and intelligent system development, with a strong emphasis on engineering applications. The program combines theoretical foundations with hands-on learning, preparing students to develop AI-powered solutions across industries such as healthcare, robotics, transportation, finance, telecommunications and software engineering.

Curriculum Structure:

Year 1:

Students begin by developing a strong foundation in artificial intelligence, mathematical modelling, programming and machine learning algorithms. Courses such as Applied Machine Learning (AAI 695), Analytical Methods in Electrical Engineering (EE 602) and Pattern Recognition and Classification (AAI 646) introduce students to neural networks, Bayesian learning, statistical pattern recognition, optimization and algorithm development. Students also learn how to apply programming and mathematical techniques to solve practical engineering problems.

Year 2:

Students advance their knowledge through specialized courses, concentration options and practical research or project work. Subjects such as Data Acquisition, Modeling and Analysis: Big Data Analytics (AAI 627), Data Acquisition, Modeling and Analysis: Deep Learning (AAI 628) and Applied Game Theory and Evolutionary Algorithms (AAI 672) help students explore large-scale data processing, deep neural networks and intelligent optimization techniques. Depending on their chosen concentration, students can apply these skills to areas such as biomedical engineering, computer engineering, electrical engineering, mechanical engineering, software engineering and systems biology, while completing a project or thesis.

Note: Stevens offers different degree options and concentration pathways. The year-wise structure above is an indicative progression rather than a fixed university-prescribed sequence.

Focus Areas:

Artificial Intelligence, Applied Machine Learning, Deep Learning, Pattern Recognition, Neural Networks, Big Data Analytics, Statistical Modelling, Computer Vision, Image Processing, Autonomous Robotics, Intelligent Communication Networks, Biomedical Engineering, Data Engineering, Software Engineering, Evolutionary Algorithms and AI-driven Engineering Solutions.

Learning Outcomes:

Graduates will be able to design and develop intelligent algorithms and AI-based systems, apply machine learning and deep learning techniques to engineering challenges, perform data acquisition and analysis, develop mathematical and computational models, evaluate algorithm performance, solve complex technical problems and communicate research findings through professional technical reports and presentations.

Professional Alignment (Accreditation):

The program is offered through the Department of Electrical and Computer Engineering within the Charles V. Schaefer, Jr. School of Engineering and Science. Stevens Institute of Technology holds institutional accreditation from the Middle States Commission on Higher Education (MSCHE). The program emphasizes practical engineering applications through hands-on laboratory experiences, research opportunities, optional thesis work, industry projects and access to facilities such as the MakerCenter and Prototype and Object Fabrication Lab.

Reputation (Employability Rankings):

Top 40 in the U.S.: Stevens was ranked among the Best Online Graduate Engineering Programs by U.S. News & World Report in 2026.
No. 1 in New Jersey: Recognized for Best Online Graduate Engineering Programs by U.S. News & World Report in 2026.
$105,000 Average Starting Salary: The average starting salary for the School of Engineering and Science Class of 2024 was $105,000 within six months of graduation.
Top 100 in the U.S.: Stevens was recognized among the Best Graduate Engineering Schools by U.S. News & World Report in 2026.
Leading Employers: Graduates have secured opportunities with organizations including AT&T, Comcast, Facebook, Goldman Sachs, Google and Microsoft.

Experiential Learning (Research, Projects, Internships etc.)

At Stevens Institute of Technology, the Master's in Applied Artificial Intelligence program is designed to provide students with hands-on experience that translates theoretical knowledge into practical skills. The curriculum emphasizes experiential learning through various projects, internships, and access to cutting-edge facilities and tools. Students engage in collaborative group projects, utilize advanced software, and participate in real-world applications of AI, ensuring they are well-prepared for the workforce.

Here are some key aspects of the experiential learning opportunities available in the program:

- State-of-the-Art Labs: Students have access to specialized labs equipped with the latest technology for AI research and development, including the AI and Machine Learning Lab.

- Collaborative Projects: The program encourages teamwork through group projects that simulate real-world challenges, allowing students to apply their skills in a collaborative environment.

- Internship Opportunities: Stevens has strong industry connections, providing students with internship opportunities at leading tech companies, where they can gain valuable experience and network with professionals.

- Software and Tools: Students work with industry-standard software such as TensorFlow, PyTorch, and MATLAB, ensuring they are proficient in the tools used in the field.

- Field Trips and Industry Visits: The program includes field trips to tech companies and research institutions, giving students insights into the latest advancements in AI and networking opportunities.

- Research Institutes: Students can engage with research initiatives at the Stevens Institute for Artificial Intelligence, where they can contribute to cutting-edge projects and publications.

- Library Resources: The university's library offers extensive resources, including access to databases and journals focused on AI and technology, supporting students' research and learning.

Progression & Future Opportunities

Pursuing a Master's in Applied Artificial Intelligence at Stevens Institute of Technology opens the door to a wealth of career opportunities in a rapidly growing field. Graduates are well-prepared for roles such as Data Scientist, Machine Learning Engineer, and AI Research Scientist, among others. The demand for skilled professionals in artificial intelligence continues to rise, making this program a strategic choice for your future:

- University Services: Stevens offers dedicated career services, including resume workshops, interview preparation, and networking events with industry leaders to help you secure internships and job placements.
- Employment Stats and Salary Figures: According to recent data, graduates from Stevens' AI programs have a high employment rate, with many securing positions within six months of graduation. The average starting salary for AI-related roles is around $100,000, reflecting the high demand for these skills.
- University–Industry Partnerships: Stevens has established partnerships with leading tech companies such as Google, IBM, and Microsoft, providing students with unique internship opportunities and real-world project experiences that enhance learning and employability.
- Long-term Accreditation Value: The program is accredited by the Middle States Commission on Higher Education, ensuring that your degree holds value and recognition in the job market for years to come.
- Graduation Outcomes: Alumni of the program have gone on to work at top-tier companies and have reported high job satisfaction, often advancing quickly in their careers due to the strong foundation provided by their education.

Further Academic Progression: After completing your Master's in Applied Artificial Intelligence, you may choose to further your studies by pursuing a Ph.D. in a related field, such as Computer Science or Data Science. This path can lead to advanced research opportunities, teaching positions at universities, or high-level roles in industry research and development. Additionally, you could explore specialized certifications in areas like machine learning or data analytics to enhance your expertise and marketability..