# Mathematics and Computer Science

## What We Do

The Department of Mathematics and Computer Science is dedicated to the preparation of students for a dynamic future. Our faculty develop curricula that will challenge your curiosity, employ your inventive facilities, and allow you to enjoy the triumph of discovery. We follow Euclid's rigorous approach to mathematics while exploring modern topics like sustainability.

The Department of Mathematics and Computer Science offers the following undergraduate degrees:

For advanced graduate study, we offer a MA Applied Mathematics, Computing, and Machine Learning and a MS Computational Biology and Biostatistics.

We offer three pathways allowing undergraduate students to complete graduate level coursework while still enrolled in their bachelor's program and reducing the time required to earn a master of arts degree:

- BS Computing and Machine Learning/MA Applied Mathematics, Computing, and Machine Learning
- BA Mathematics/MA Applied Mathematics, Computing, and Machine Learning
- BS Mathematics/MA Applied Mathematics, Computing. and Machine Learning
- BS Biology/MS Computational Biology and Biostatistics

Our faculty are active researchers who provide an outstanding learning environment for students. Their research interests are diverse and include pure mathematics, applied mathematics, computer science, functional analysis, algebra, differential geometry, and topology.

### Department Contact

David Rosenthal, Ph.D.

Professor and Chair

[email protected]

## Mathematics and Computer Science Minors

The minor in Applied Mathematics requires the successful completion of 21 credits.

#### Required

- MTH 1730 University Calculus I
- MTH 1740 University Calculus II
- MTH 2750 University Calculus III

#### Choose three from among the following:

- CSC 1380 Introduction to Computer and Data Science or CSC 1390 Computer Programming with Calculus Applications
- MTH 2390 Introduction to Operations Research
- CSC 2600/MTH 3350 Machine Learning, Neural Networks and Deep Learning
- CSC 2630/MTH 3390 Introduction to Artificial Intelligence
- CSC 2720 Computability and Automation
- MTH 2790 Introduction to Linear Algebra
- MTH 3310 Design and Analysis of Algorithms
- MTH 3320 Introduction to Machine Learning
- MTH 3330 Data Security and Cryptography
- MTH 3340 Foundations of Data Science
- MTH 3350 Advanced Machine Learning, Neural Networks, and Deep Learning
- MTH 3360 Quantum Computing and Quantum Information Science
- MTH 3370 Machine Learning for Finance
- MTH 3380 Discrete Mathematics
- MTH 3810 Mathematical Theory of Probability and Statistics
- MTH 3840 Ordinary Differential Equations
- MTH 3850 Partial Differential Equations
- MTH 3860 Numerical Analysis
- MTH 3970 Topics in Applied Mathematics
- MTH 4830 Complex Variables
- CSC 2600/MTH 3350 Machine Learning, Neural Networks and Deep Learning

The Computer Science minor requires the completion of 15 credits, including the following:

- CSC 1400; 1410 Computer Science I; II

Students in the minor must also choose three courses from among the following:

- CSC 1350 Commercial Computing
- CSC 1470 Advanced Programming
- CSC 2420 Logical Design and Computer Architecture
- CSC 2430 Computer Organization
- CSC 2440 Compiler Design
- CSC 2450 Programming Languages
- CSC 2460 Simulation
- CSC 2470 Operating Systems
- CSC 2480 Algorithms and Data Structures
- CSC 2490 Databases
- CSC 2500 Data Security and Cryptography
- CSC 2510 Foundations of Data Science
- CSC 2520 Quantum Computing and Quantum Information Science
- CSC 2580 Design and Analysis of Algorithms
- CSC 2590 Introduction to Machine Learning
- CSC 2600 Advanced Machine Learning, Neural Networks, and Deep Learning
- CSC 2640 Networking I-TCP/IP
- CSC 2720 Computability and Automata

The minor in Computing, available on both the Queens and Staten Island campuses, requires the successful completion of 15 credits chosen in consultation with an advisor.

#### Required

- CSC 1400 Computer Science I
- CSC 1410 Computer Science II
- CSC 1470 Advanced Programming
- CSC 2450 Programming Languages
- CSC 2490 Databases

Please note that students who have completed MTH 1730 or equivalent can replace CSC 2450/2490 with any of the following:

- CSC 2510/MTH 3340 Foundations of Data Science
- CSC 2580/MTH 3310 Design and Analysis of Algorithms
- CSC 2590/MTH 3320 Introduction to Machine Learning
- CSC 2600/MTH 3350 Machine Learning, Neural Networks and Deep Learning
- CSC 2630/MTH 3390 Introduction to Artificial Intelligence
- CSC 2720 Computability and Automation

The Data Science minor requires the completion of 16-17 credits.

#### Required Courses

Calculus | MTH 1220 or MTH 1730 | 4 credits |

Statistics | MTH 1020, MTH 1210, or equivalent | 3-4 credits |

CSC 1380 | Introduction to Computer and Data Science | 3 credits |

#### Electives

Choose two courses (six credits) from among the following:

- MTH 1040 Mathematical Models for Decision Making
- CSC 2600/MTH 3350 Machine Learning, Neural Networks and Deep Learning
- CSC 2630/MTH 3390 Introduction to Artificial Intelligence
- CSC 2720 Computability and Automation
- MTH 3310 Design and Analysis of Algorithms
- MTH 3320 Introduction to Machine Learning
- MTH 3970 Topics in Applied Mathematics
- MTH 4970 Independent Research in Statistics and Its Applications

The 18-credit Information Science minor requires completion of the following courses:

- CSC 1020 Principles of Computer Science
- CSC 1350 Commercial Computing or CSC 1400 Computer Science I
- CSC 2490 Databases

Students must also choose three from the following elective courses:

- CSC 1410 Computer Science II
- CSC 1470 Advanced Programming
- CSC 2450 Programming Languages
- CSC 2480 Algorithms and Data Structures
- CSC 2640 Networking I-TCP/IP

Machine learning is a branch of artificial intelligence that is based on the idea that systems can learn from data, identify patterns, and make decisions with minimal human intervention. It provides methods for automating the process of analytical model building and has rapidly developing applications in many different areas such as actuarial sciences, finance, and healthcare.

The minor in Machine Learning requires the successful completion of 15-17 credits, chosen in consultation with an advisor.

#### Required

- CSC 1030 Machine Learning for Everyone
- MTH 1220/1260/1320/1730 Calculus
- MTH 1020/1210/3810 or PSY 2030 or SOC 2610 Statistics
- CSC 2590/MTH 3320 Introduction to Machine Learning

#### Choose one of the following:

- CSC 2510/MTH 3340 Foundations of Data Science
- CSC 2580/MTH 3310 Design and Analysis of Algorithms
- CSC 2600/MTH 3350 Machine Learning, Neural Networks and Deep Learning
- CSC 2630/MTH 3390 Introduction to Artificial Intelligence
- CSC 2620/MTH 3370 Machine Learning for Finance
- CSC 2720 Computability and Automation
- CSC 4980/MTH 4980 Independent Research in Machine Learning and Artificial Intelligence

The Mathematics minor requires completion of the following courses, for a total of 21 credits:

- MTH 1730; 1740 University Calculus I; II
- CSC 1380 Introduction to Computer and Data Science or CSC 1390 Computer Programming with Calculus Applications
- MTH 2700 Introduction to Mathematical Thinking
- MTH 2750 University Calculus III
- MTH 2790 Introduction to Linear Algebra