Master's Degree in Machine Learning

1 Years On Campus Masters Program

Stevens Institute of Technology

Program Overview

The Master of Science in Machine Learning at Stevens Institute of Technology provides students with a strong foundation in machine learning theory, statistical modelling, artificial intelligence and practical applications of intelligent technologies. Designed for students interested in advancing careers in technology, research and data-driven industries, the program develops the expertise needed to design and apply machine learning solutions across fields such as healthcare, finance, robotics, computer vision and natural language processing.

Curriculum Structure:

Year 1:

Students begin by developing a strong understanding of artificial intelligence, statistical methods and fundamental machine learning techniques. Core subjects such as Artificial Intelligence, Machine Learning: Fundamentals and Applications, and Statistical Machine Learning introduce students to predictive modelling, supervised and unsupervised learning, algorithm development and data-driven decision-making.

Year 2:

Students advance their technical expertise through specialized coursework and electives covering deep learning, language technologies and intelligent information systems. Courses such as Deep Learning, Natural Language Processing, and Text Mining and Information Retrieval help students explore advanced machine learning applications, develop analytical models and prepare for research-oriented or industry-focused projects.

Focus Areas:

Artificial Intelligence, Machine Learning Algorithms, Statistical Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Predictive Analytics, Data Mining, Intelligent Systems, Information Retrieval, Robotics and Applied Machine Learning.

Learning Outcomes:

Graduates will be able to understand the theoretical foundations of machine learning algorithms, develop statistical learning models, select appropriate predictive and statistical methodologies, apply machine learning techniques to real-world problems, make data-driven decisions and interpret classification and regression results while evaluating the strengths and limitations of different models.

Professional Alignment (Accreditation):

The program is offered through the Stevens School of Computing and provides industry-oriented preparation through theoretical coursework, practical learning opportunities and research exposure. Students can also explore cooperative education, research opportunities, laboratory experiences and optional thesis work. The university does not identify a separate program-specific professional accreditation on the official program page.

Reputation (Employability Rankings):

Top 25 in the U.S.: Stevens was ranked among the top 25 Best Online Graduate Information Technology Programs by U.S. News & World Report in 2026.
89% Employment Rate: The average employment rate for the program's Class of 2024 was 89% within six months of graduation.
$121,000 Average Salary: Mean compensation for Machine Learning program graduates in the Class of 2023 was $121,000.
CSRankings: Stevens ranks 59th in the U.S. for Machine Learning and 78th for Artificial Intelligence, according to the university's published statistics.
Industry Opportunities: Graduates have secured employment with leading organizations including Amazon, Bloomberg, Facebook, Google, IBM and Intel.

Experiential Learning (Research, Projects, Internships etc.)

At Stevens Institute of Technology, the Master's Degree in Machine Learning is designed to provide students with a robust blend of theoretical knowledge and practical skills. The program emphasizes experiential learning, ensuring that you not only understand the concepts but also apply them in real-world scenarios. Students have access to state-of-the-art facilities and cutting-edge tools that enhance their learning experience and prepare them for the demands of the industry.

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

- Advanced Computing Labs: Utilize high-performance computing resources equipped with the latest hardware and software for machine learning research and projects.
- Collaborative Projects: Engage in group projects that simulate real-world challenges, allowing you to work alongside peers and faculty to develop innovative solutions.
- Internship Opportunities: Benefit from partnerships with leading tech companies and organizations, providing you with valuable internship experiences that enhance your resume and professional network.
- Research Centers: Access specialized research centers, such as the Stevens Institute of Artificial Intelligence, where you can collaborate on cutting-edge research and contribute to ongoing projects.
- Industry-Standard Software: Gain proficiency in essential machine learning tools and software, including TensorFlow, PyTorch, and MATLAB, which are widely used in the industry.
- Field Trips and Workshops: Participate in field trips to tech companies and workshops led by industry experts, giving you insights into current trends and practices in machine learning.
- Library Resources: Take advantage of extensive library resources, including access to academic journals, databases, and research materials that support your studies and projects.

Progression & Future Opportunities

Pursuing a Master's Degree in Machine Learning at Stevens Institute of Technology opens the door to a wealth of career opportunities in a rapidly growing field. Graduates often find themselves in high-demand roles such as Machine Learning Engineer, Data Scientist, AI Research Scientist, and Business Intelligence Analyst. The skills and knowledge gained from this program position you for success in various industries, from tech to finance and healthcare.

Here’s what you can expect in terms of progression and future opportunities:

- University Services: Stevens offers dedicated career services, including resume workshops, interview preparation, and networking events with industry leaders. The Career Center also hosts job fairs specifically tailored to tech and engineering fields.

- Employment Stats and Salary Figures: According to recent data, over 90% of Stevens graduates secure employment within six months of graduation, with starting salaries averaging around $100,000 for roles in machine learning and data science.

- University–Industry Partnerships: Stevens has established partnerships with leading companies such as Google, IBM, and Amazon, providing students with internship opportunities and real-world projects 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 from the program have gone on to work at prestigious organizations and have reported significant career advancement, often moving into leadership roles within just a few years of graduation.

Further Academic Progression: After completing your Master's in Machine Learning, you may choose to further your studies by pursuing a Ph.D. in Computer Science or a related field. This path can lead to advanced research opportunities, teaching positions at universities, or specialized roles in cutting-edge technology development. Additionally, you could explore certifications in specific machine learning frameworks or tools to enhance your expertise and marketability in the job market.