Meet a Growing Demand in an Accelerating Field
Mathematics, particularly the field of applied mathematics, is accelerating rapidly. Applied Mathematics, Computing, and Machine Learning professionals work in almost every field and sector—both public and private—including some of the most up-and-coming areas such as clean energy, climate modeling, data mining, machine learning and artificial intelligence, personalized medicine, supply chain, and more.
- Degree Type
- MA
- Area of Interest
- Science & Mathematics
- Associated Colleges or Schools
- Program Location
- Queens Campus
- Required Credit Hours
- 33
Where the Theoretical Meets the Practical: Applied Mathematics, Computing, and Machine Learning in the Real World
Applied mathematics, computing, and machine learning have the ability to transcend the theoretical by placing value and providing clarity. This field deftly bridges the gap between theoretical knowledge and practical applications, validating and refining theories, and enabling new discoveries.
Unlike programs that focus solely on pure mathematics or computer science, St. John’s distinctive degree program offers deep knowledge of theoretical mathematics as it also strengthens your familiarity with the procedures and algorithms that underlie computation.
Gain Career-Ready Skills
By earning your master’s in applied mathematics, computing, and machine learning, you gain the skills needed to succeed in some of the most sought-after (and rapidly growing) careers. No matter which field you’re interested in, you can pursue various careers with an M.A. in Applied Mathematics, Computing, and Machine Learning.
- Analyst
- Analytics Consultant
- Analytics Manager
- Applied Mathematics Researcher
- Biostatistician
- Business Analyst
- Cryptographer
- Data Analyst
- Data Engineer
- Forecast Analyst
- Functional Analyst
- Global Pricing Analyst
- Guidance and Navigation Engineer
- Informatics Scientist
- Information Analyst
- Mathematics Instructor
- Modeling Engineer
- Operations Research Analyst
- Pharmacokinetic / Pharmacodynamic Modeler
- Principal Scientist
- Quantitative Developer
- Quantitative Pharmacologist
- Quantitative Scientist
- Quantitative Software Engineer
- Research Scientist
- Risk Analyst
- Risk Strategist
- Simulation Engineer
- Supply Chain Analyst
- Software Architect
- Systems Engineer
Program at a Glance
M.A. in Applied Mathematics, Computing degree awarded
Degree Credits Required
Years (Full Time)
Estimated Time to Complete
Courses Begin
Fall/Spring
Crafting the future of the industry at St. John’s with our cutting-edge Machine Learning Institute
We know how important it is to stay at the forefront of the complex industry of machine learning. That’s why we created the Machine Learning Institute (MLI).
The Machine Learning Institute at St. John’s University addresses the rising demand of machine learning in research, the sciences, and engineering. It offers exciting lectures and minicourses to help you prepare for this rapidly growing and evolving field. Here are just some of the topics covered by the MLI mini courses:
- Python programming, and crash courses in linear algebra and multidimensional calculus
- Introduction to complexity and its application to modeling and games
- Reinforcement learning, time series, and application to finance
- Deep Learning using PyTorch
- Google toolbox for Data Science
Why St. John’s University?
There’s nothing quite like hands-on, real-world experience to prepare you for a career in applied mathematics, computing, and machine learning.
Low student-teacher ratio for increased interaction and individualized research opportunities
Study among the best, most influential employers in the nation
Learn from specialized, experienced experts
“As a student in the Applied Mathematics, Computing, and Machine Learning master’s program, I had a
great experience with 1:1 mentorship with professors, especially with research projects. They always set aside time to help with any questions or concerns.” -Alexis P. Adams ’23G
“My master’s from St. John’s has been extremely important (and a game changer) in my career. Thanks to all the combined analytical, research, and soft and hard skills developed through studying at St. John’s, I am able to deliver business value in my role as a Business Data Analyst for the New York City Department of Health.” -Ismael Monsegnur ’20G
Scholarships
All students are eligible to receive merit-based scholarships upon application (including international students). Scholarships are prorated by the number of credits a student takes per semester. There are no specific scholarships from the department. However, students in this program are eligible for the US National Science Foundation Robert Noyce Teacher Scholarship Program should they be interested in teaching middle or high school.
Degree Requirements
The M.A. requires the successful completion of 33 credits of coursework and a coursework examination.
You are required to complete one of the following from each section:
- MTH 165 Introduction to Computing with Applications
- MTH 169 Computing with Statistical Applications
- MTH 177 Software Systems
- MTH 209 Linear Algebra
- MTH 213 Applied Algebra, Coding, and Combinators
- MTH 214 Cryptography
- MTH 161 Introduction to Probability
- MTH 163 Statistical Modeling
- MTH 164 Statistics and Data Analytics
- MTH 182 Machine Learning in Finance
- MTH 222 Machine Learning
- MTH 228 Introduction to Modern Topics in Machine Learning
- MTH 242 Artificial Intelligence
- MTH 284 Statistical Natural Language Processing
- MTH 286 Reinforcement Learning in Finance
- MTH 290 Advanced Machine Learning
- MTH 180 Computer Algorithms
- MTH 276 Automata & Formal Language Theories
- MTH 283 Combinatorial Optimization
(Must complete both)
- MTH 580 Database Management Systems
- MTH 105 or MTH 105T Comprehensive Examination or Master’s Thesis
Students must also complete five elective courses. Courses include:
- MTH 161 Introduction to Probability
- MTH 163 Statistical Modeling
- MTH 164 Statistics and Data Analytics
- MTH 165 Introduction to Computing with Applications
- MTH 167 Mathematical Modeling
- MTH 169 Computing with Statistical Applications
- MTH 172 Operations Research I
- MTH 177 Software Systems
- MTH 180 Computer Algorithms
- MTH 182 Machine Learning in Finance
- MTH 209 Linear Algebra
- MTH 213 Applied Algebra, Coding, and Combinatorics
- MTH 214 Cryptography
- MTH 222 Machine Learning
- MTH 228 Introduction to Modern Topics in Machine Learning
- MTH 242 Artificial Intelligence
- MTH 276 Automata & Formal Language Theories
- MTH 282 Convex Optimization
- MTH 283 Combinatorial Optimization
- MTH 284 Statistical Natural Language Processing
- MTH 286 Reinforcement Learning in Finance
- MTH 290 Advanced Machine Learning
- MTH 600 Topics in Applied and Computational Mathematics
Meet Our Faculty
Contact Us
We are here to answer any questions you may have about the M.A. in Applied Mathematics, Computing, and Machine Learning degree program and the admission process.
Interested in Science & Mathematics, but not sure if Applied Mathematics, Computing, and Machine Learning, Master of Arts (M.A.) is right for you?
Take the Next Step
Explore Affordability
The Office of Student Financial Services is committed to providing students and their families with the information they need to navigate and understand the financial aid and payment process.
Apply to St. John's
St. John’s offers a free online application for all 100+ undergraduate programs, and graduate applications carry a low cost for most programs.