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Applied Mathematics, Computing, and Machine Learning, Master of Arts

Math and Computer Science

Overview

Earn a master's degree in Applied Mathematics, Computing, and Machine Learning from St. John's University in New York City!

The versatile Master of Arts (M.A.) in Applied Mathematics, Computing, and Machine Learning at St. John’s will prepare you for immediate and lucrative employment in a wide range of high-growth career fields that include data science, health care, climatology, materials science, digital imagery, and finance, just to name a few.

Unlike programs that focus solely on pure mathematics or computer science, this distinctive degree program offers you deep knowledge of theoretical mathematics alongside familiarity with the procedures and algorithms that underlie computation.

Through the 33-credit program, you will use computer programs and machine learning algorithms to solve real-world mathematical problems. You’ll develop and analyze mathematical models of physical and biological phenomena and engineering systems, interpret the solutions to these problems in the context of what they model, and use the results to identify relationships, patterns, and the effects of altering one or more variables or modeling assumptions. Machine Learning applications include computer vision, email filtering, marketing, robotics, and speech recognition.

Courses covering such topics as software systems, computer algorithms, machine learning, formal language theories, and database management systems will provide you with the research, analytical, and communication skills to succeed in any career path you choose. Thanks to our small class sizes, you’ll receive individual attention from faculty to guide your research and help you make career connections. Full-time students can complete the degree in two years, with classes scheduled to accommodate working professionals.

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Department Faculty

Please see a list of our Mathematics and Computer Science faculty.

Department Contact

St. John's University crest on the top of the gate

Genady Ya. Grabarnik, Ph.D.

Professor and Program Director

St. John Hall, Room 334F
718-990-2467
[email protected]

Courses

The M.A. requires successful completion of 33 credits of coursework and a coursework examination. Students of the program are required to take:

Computing (Choose One):

  • MTH 165 Introduction to Computing with Applications
  • MTH 169 Computing with Statistical Applications
  • MTH 177 Software Systems

Probabilistic/Statistical Methods (Choose One):

  • MTH 161 Introduction to Probability
  • MTH 163 Statistical Modeling
  • MTH 164 Statistics and Data Analytics

Algorithmic Methods (Choose One):

  • MTH 180 Computer Algorithms
  • MTH 276 Automata & Formal Language Theories
  • MTH 283 Combinatorial Optimization

Algebraic Methods (Choose One):

  • MTH 209 Linear Algebra
  • MTH 213 Applied Algebra, Coding, and Combinators
  • MTH 214 Cryptography

Machine Learning and Artificial Intelligence (Choose One):

  • 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

Other Required Courses:

  • MTH 580 Database Management Systems
  • MTH 105 or MTH 105T  Comprehensive Examination

Elective Courses (Choose Five):

  • 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

Admission

You can find more information about admission to this master’s program on the Graduate Admissions page.

International Students
International applicants may find more information on our International Admission and International Students and Scholars pages.

Contact Information
Office of Graduate Admission
718-990-1601
[email protected]

Tuition and Financial Aid

The Department of Mathematics and Computer Sciences offers a limited number of academic graduate assistantship positions each year on a highly competitive basis. These positions provide tuition remission and a stipend and involve assisting faculty with their research. Non-academic graduate assistantships, which also offer tuition remission and a stipend, are available throughout the University. For more information about assistantships, please visit the Graduate Admissions page.

For information about other forms of financial aid, please visit Tuition and Financial Aid.

Career Outcomes

The M.A. in Applied Mathematics, Computing, and Machine Learning is a versatile and in-demand degree for employment. Effective use of advanced applied mathematical techniques has become increasingly important in industrial, business, and scientific settings, which rely on sophisticated software to solve complex problems. The ability to construct and analyze specific mathematical models and develop and efficiently execute computational mathematical algorithms is needed in virtually any field.

Once you graduate with your M.A., you’ll be able to pursue further doctoral study in mathematics or find immediate employment related to high growth fields such as: materials science; machine learning and artificial intelligence; computer animation and digital imagery; finance and economics; ecology; systems biology; climatology; and epidemiology.

Employers seeking candidates with advanced degrees in applied mathematics include:

Aerospace and Transportation Equipment Manufacturers

Academic Institutions and Research Institutes

Chemical or Pharmaceutical Manufacturers

Communications Service Providers

Computer Information and Software Firms

Consulting Firms

Consumer Products Companies

Government Laboratories, Research Offices, and Agencies

Electronics and Computer Manufacturers

Energy Systems Firms

Engineering Research Organizations

Federally-Funded Contractors

Financial Service and Investment Management Firms

Medical Device Companies

Technology Companies

Transportation Service Providers

Additional Information

Because of the low student-to-faculty ratio within the mathematics program, you will be able to work closely with professors on independent research in preparation for your career. The Department of Mathematics and Computer Science will also notify you of potential internship opportunities as they become available, and will assist you in the internship application process as needed. Our faculty members are active scholars who are dedicated to helping each student succeed.