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Online Machine Learning Master's Program

Program Details


Master of Science


On Campus & Online


Graduate Admissions1.888.511.1306graduate@stevens.edu
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Our Machine Learning Master's program is designed to equip students with the knowledge and skills to pioneer the next technological revolution. As machine learning and related disciplines continue to advance, their impact will soon extend to every facet of technology.  

USWNR 2024 Best Online Grad Computer Information Technology BadgeMachine learning is a rapidly expanding field with a vast range of applications across various domains, including intelligent systems, computer vision, speech recognition, natural language processing, robotics, finance, information retrieval, bioinformatics, healthcare, and weather prediction. 

Our exceptional Machine Learning Master's program offers a comprehensive curriculum that not only establishes a solid foundation in theoretical concepts but also ensures practical proficiency. You will gain an in-depth understanding of deep learning theory and become well-versed in the most important paradigms. This knowledge will empower you to apply existing methods or develop new approaches for real-world applications. Whether you aspire to pursue a career in industry, academia, or research, our program prepares you to excel in your chosen path.

Below is a suggested term-by-term sequence of courses:

Term 1

Term 2

Additional Core Courses

Choose at least 2 from this list to fulfill the core course requirements:

*Elective Concentration Courses

In addition to the above four required courses, students can choose from three additional elective courses. The following can be found in Academic Catalog and offer an online section:


BIA 654 Experimental Design II - 3 Credits

BIA 660 Web Mining - 3 Credits

BIA 662 Cognitive Computing - 3 Credits

BIA 678 Big Data Technologies - 3 Credits

CPE 608 Applied Modeling & Optimization - 3 Credits

CPE 695 Applied Machine Learning - 3 Credits

FE 541 Applied Statistics with Applications in Finance - 3 Credits

MA 541 Statistical Methods - 3 Credits

MA 630 Advanced Optimization Methods - 3 Credits

MA 641 Time Series Analysis I - 3 Credits


The remaining three courses can be any general elective approved by the student's advisor or academic department.