Applied Mathematics: Data Science and Cryptography (BS)

Applied Mathematics: Data Science and Cryptography (BS)

The Applied Mathematics major has two concentrations, Data Science and Cryptology.  The Data Science concentration presents the principles of data representation, big data management, and statistical modeling.  Students learn to use modern computing techniques to reveal hidden causal and temporal relationships within large data sets.  Hidden information is often benign but it might also be evidence of malevolent activities that have already occurred or are in progress.  Cryptology is the science of both personal and institutional data security.  Students learn to secure information, maintain data integrity, authenticity, and non-reputability.  Cryptologists play a vital role in detecting events yet to unfold, especially when attempting to interdict and thwart incipient cyber intrusions and terrorist attacks.

The curriculum offers an integrated academic program with the depth and breadth necessary to make graduates truly competitive in the job market.  Both concentrations provide the knowledge and the skills that are in demand in high tech entrepreneurship, finance, modern communications, medicine, security, transportation, and manufacturing.  The New York City metropolitan region is being repositioned as a nexus of technological innovation and discovery as well as a haven for entrepreneurial leadership.  Such a metamorphosis requires the availability of a renewable work force possessing skills in data analysis and data security.  Consequently, employment opportunities are expected to be available for applied mathematics graduates for the foreseeable future.

Those individuals that opt to undertake graduate study will find that they are well prepared to enroll in a wide range of Masters and Doctoral programs such as Digital Forensics and Cyber Security, Financial Mathematics, Machine Learning, traditional Mathematics, and Mathematics Education.  Indeed, the required mathematics core aligns well with the core requirements of other CUNY mathematics programs thereby affording graduates the widest possible choice of subsequent educational opportunities.

Learning Outcomes.  Students will:

• Apply the principles of mathematical proof and deductive logic to prove level appropriate mathematical statements or create counterexamples with the context of the real number axioms and the axioms defining various algebraic structures.
• Apply the mathematical modeling process to modern problems in data science and cryptography for the purpose of analyzing large data sets and encrypting plain text or decrypting cipher text.
• Function effectively in an interdisciplinary team environment and express quantitative information effectively to others.
• Identify and adhere to the ethical constraints of respecting personal data privacy and evaluate and assess ethical standards for the application of cryptographic algorithms in contemporary contexts. 

Credits Required.

Applied Mathematics: Data Science & Cryptography Major  


General Education




Total Credits Required for B.S. Degree


Coordinator.  Professor Samuel Graff, Department of Mathematics and Computer Science (212-237-8767,

Advisors. Professors Michael Puls (212.484.1178,, Hunter Johnson (212.237.8846,, Antoinette Trembinska (212.237.8838,, Shaobai Kan (646.557.4866,, Peter Shenkin (212.237.8925,, Department of Mathematics and Computer Science.

FOUNDATIONAL COURSES                                                                                           Subtotal: 0-3 credits

May be required depending on mathematics placement

MAT 141



Advisor recommendation: MAT 141 fulfills the Required Core: Mathematics and Quantitative Reasoning area of the Gen Ed Program.

PART ONE. CORE COURSES                                                                                            Subtotal: 15 credits

CSCI 271 Introduction to Computer Science
CSCI 272 Object-Oriented Programming
MAT 204 Discrete Structures
MAT 241 Calculus I
MAT 242 Calculus II

PART TWO. MATHEMATICS CORE COURSES                                                         Subtotal: 18 credits

MAT 243 Calculus III
MAT 244 Calculus IV
MAT 301 Probability & Mathematical Statistics I
MAT 310 Linear Algebra
MAT 351 Introduction to Ordinary Differential Equations
CSCI 373 Advanced Data Structures

PART THREE. CONCENTRATIONS                                                                               Subtotal: 12 credits

Students must choose one concentration and complete four courses

Concentration A. Data Science

Data Science plays a critical role in analyzing large data sets which may have valuable information that is obscured by the sheer volume of the data itself.  In the Data Science concentration, students will learn the principles of data representation, big data management, and statistical modeling. They will also be able to use computers to reveal hidden causal and temporal relationships in large data sets.

Learning outcomes for Data Science Concentration. Student will:

• Use mathematical methods to analyze and recognize the properties of large data sets as well as any anomalies.
• Use suitable models such as linear regression, logical regression, to analyze data and predict probability distributions.
• Recognize clustering in large data sets and explain its significance.

CSCI 362 Databases and Data Mining
MAT 302 Probability and Mathematical Statistics II
MAT 3XX Multivariate Analysis
MAT 4YY Data Analysis Capstone

Concentration B. Cryptography

Cryptography is the science of data security, both personal and institutional, and as such is also an important component of justice.  In the Cryptography concentration, students will learn to secure information which is achieved by assuring privacy as well as other properties of a communication channel, such as data integrity, authenticity, and non-reputability, depending upon the application. They will devise systems for companies to resist the unwarranted intrusions of hackers, to protect internal company and consumer data, and to act as consultants to research staff concerning the implementation of cryptographic and mathematical methods.

Learning outcomes for the Cryptography Concentration. Students will:

• Use the mathematics upon which specific cryptographic algorithms are based to analyze the strengths and weaknesses of cryptographic schemes.
• Guarantee authenticity and integrity of data and ensure that transactions are non-repudiable, when appropriate.
• Develop cryptographic algorithms.

CSCI 360 Cryptography and Cryptanalysis
MAT 341 Advanced Calculus 1
MAT 410 Abstract Algebra
MAT 4XX Mathematical Cryptography Capstone

PART FOUR. ELECTIVES                                                                                                     Subtotal: 6 credits

Choose two
MAT 323 Operations Research Models I
MAT 324 Operations Research Models II
MAT 352 Applied Differential Equations
MAT 371 Numerical Analysis
MAT 380 Selected Topics in Mathematics
MAT 442 Advanced Calculus 2

                                                                                                                                           Total Credit Hours: 51-54

                                                                                                                                              Last Updated: 12/19/17