Engineering Science (AI and Data Innovation) MS

2 Years On Campus Masters Program

University at Buffalo SUNY

Program Overview

The Engineering Science (AI and Data Innovation) MS at the University at Buffalo combines artificial intelligence, data science and engineering to prepare students to develop intelligent systems and solve complex real-world problems. The programme focuses on statistical learning, machine learning, data analytics, natural language processing and computer vision, making it suitable for students interested in careers across technology, healthcare, finance, energy and other data-driven industries.

Curriculum Structure

The programme requires 30 credits, comprising 18 credits of core courses, 9 credits of electives and a 3-credit culminating capstone experience. Students develop foundational technical knowledge before progressing to specialised AI and data science applications through elective courses and practical projects.

Year 1 – Core AI and Data Science Foundations

Students build a strong foundation in mathematics, statistics, machine learning and computational techniques. Core courses include Numerical Math for Computing and Data Science (EAS 501), Probability Theory (EAS 502), Statistical Learning and Data Mining I (EAS 508), Intro to Machine Learning (EAS 574), Basics of AI (EAS 510) and Data Intensive Computing (EAS 587). These subjects help students develop the analytical and programming skills needed to design intelligent systems and process large datasets.

Year 2 – Advanced Specialisation and Practical Application

Students deepen their knowledge through electives in advanced machine learning, artificial intelligence and data analytics. Available subjects include Statistical Learning for Data Mining 2 (EAS 509), Reinforcement Learning (CSE 546), Pattern Recognition (CSE 555), Deep Learning (CSE 676), Computer Vision and Image Processing (CSE 573) and Natural Language Processing and Text Mining (CSE 635). Students complete their studies through an internship or applied research project, gaining practical experience in solving industry-related or interdisciplinary engineering problems.

Note: The year-wise structure is indicative. The university states that the programme can be completed in approximately 1 to 1.5 years.

Focus Areas

Artificial Intelligence, Machine Learning, Statistical Learning, Data Mining, Big Data Analytics, Data-Intensive Computing, Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Pattern Recognition, Predictive Analytics, Computational Mathematics, Healthcare Analytics, Optimization Methods, AI Systems Engineering.

Learning Outcomes

Graduates develop the ability to apply statistical and mathematical methods to data-driven problems, design and implement machine learning models, develop intelligent AI systems, manage large-scale datasets and use advanced analytical techniques. They also gain practical experience in interdisciplinary engineering applications, scalable computing and real-world problem-solving through internships or applied research projects.

Professional Alignment (Accreditation)

The programme is offered through the University at Buffalo's School of Engineering and Applied Sciences and is officially registered with the New York State Education Department. It is also STEM-approved, allowing eligible international students to apply for the 24-month STEM OPT extension in the United States.

Reputation (Employability Rankings)

The programme is designed around emerging industry requirements in artificial intelligence and data science. Students gain practical exposure through industry internships, faculty-led applied research and experiential projects. The university identifies career opportunities in AI Systems Engineering, Data Science and Analytics, Machine Learning, Natural Language Processing, Computer Vision and Intelligent Automation. A programme-specific employability ranking or graduate employment rate is not published on the official programme page.

Experiential Learning (Research, Projects, Internships etc.)

At the University at Buffalo, the MS in Engineering Science with a focus on AI and Data Innovation offers students a unique opportunity to gain practical skills that are essential in today’s technology-driven world. The program emphasizes hands-on learning through various facilities and tools designed to enhance your educational experience. Students engage in real-world projects, collaborate with peers, and utilize cutting-edge technology to prepare for careers in artificial intelligence and data science.

Here’s how you can expect to gain experiential learning through this program:

- State-of-the-Art Laboratories: Access to specialized labs such as the Data Science and AI Lab, where you can work on innovative projects using advanced computing resources.
- Collaborative Projects: Engage in group projects that simulate real-world challenges, allowing you to apply theoretical knowledge to practical situations.
- Internship Opportunities: The program encourages internships with industry partners, providing you with valuable work experience and networking opportunities.
- Digital Tools and Software: Utilize industry-standard software such as Python, R, TensorFlow, and MATLAB for data analysis and machine learning projects.
- Field Trips: Participate in field trips to tech companies and research institutions, giving you insights into the latest industry trends and practices.
- Research Institutes: Collaborate with faculty at research institutes like the UB Artificial Intelligence Institute, where you can contribute to groundbreaking research.
- Access to Libraries: Benefit from extensive library resources, including databases and journals specific to engineering and data science, to support your studies and research.

These experiential learning opportunities are designed to ensure that you not only understand the theoretical aspects of AI and data innovation but also gain the practical skills needed to excel in your career.

Progression & Future Opportunities

The MS in Engineering Science (AI and Data Innovation) at the University at Buffalo SUNY prepares graduates for a dynamic career landscape, equipping them with the skills needed to excel in various high-demand roles. Graduates often find themselves in positions such as Data Scientist, AI Engineer, Machine Learning Specialist, and Business Intelligence Analyst. With the rapid growth of AI and data-driven technologies, the opportunities for advancement in these fields are abundant.

Here’s how the University at Buffalo supports your journey toward a successful career:

- Career Services: The university offers dedicated career counseling, resume workshops, and interview preparation sessions to help you stand out in the job market.
- Employment Statistics: Graduates from this program have a strong employment rate, with many securing positions within six months of graduation. The average starting salary for graduates in related fields is around $85,000, reflecting the high demand for skilled professionals.
- University–Industry Partnerships: The program has established partnerships with leading tech companies and organizations, providing students with internship opportunities and real-world project experience that enhances their learning.
- Accreditation Value: The program is accredited by relevant professional bodies, ensuring that your degree holds long-term value and recognition in the industry.
- Graduation Outcomes: Alumni have successfully transitioned into influential roles in top companies, contributing to innovative projects and advancements in AI and data science.

Further Academic Progression: After completing the MS in Engineering Science (AI and Data Innovation), you may choose to pursue a Ph.D. in a related field, which can open doors to advanced research opportunities and academic positions. Additionally, you could explore certifications in specialized areas such as data analytics, machine learning, or artificial intelligence to further enhance your expertise and career prospects. The University at Buffalo provides resources and guidance for those interested in continuing their education, ensuring you have the support needed to achieve your academic and professional goals.