Computational Mathematics Bachelor of Science Degree
Computational Mathematics
Bachelor of Science Degree
 RIT /
 Rochester Institute of Technology /
 Academics /
 Computational Mathematics BS
RIT’s computational mathematics major emphasizes problemsolving using mathematical models to identify solutions in business, science, engineering, and more.
Overview for Computational Mathematics BS
Why Major in Computational Mathematics at RIT
Learn by Doing: Gain experience through an experiential learning component of the program approved by the School of Mathematics and Statistics.
Real World Experience: With RIT’s cooperative education and internship program you'll earn more than a degree. You’ll gain practical handson experience that sets you apart.
Strong Career Paths: Recent computational mathematics graduates are employed at Carbon Black, iCitizen, Amazon, National Security Agency, KJT Group, Department of Defense, and Hewlett Packard.
Accelerated Bachelor’s/Master’s Available: Earn both your bachelor’s and your master’s in less time and with a cost savings, giving you a competitive advantage in your field.
STEMOPT Visa Eligible: The STEM Optional Practical Training (OPT) program allows fulltime, oncampus international students on an F1 student visa to stay and work in the U.S. for up to three years after graduation.
What is Computational Mathematics?
Computational mathematics, or computational and applied mathematics, focuses on using numerical methods and algorithms to solve mathematical problems and perform mathematical computations with the aid of computers. It bridges the gap between theoretical mathematics and practical applications in various fields, including science, engineering, finance, and more.
RIT’s Computational Mathematics Major
The computational mathematics bachelor's degree combines the beauty and logic of mathematics with the application of today’s fastest and most powerful computers. At RIT, you get the solid foundation in both mathematics and computational methods that you need to be successful in the field or in graduate school.
RIT’s computational mathematics major uses computers as problemsolving tools to come up with mathematical solutions to realworld problems in engineering, operations research, economics, business, and other areas of science.
Computational Mathematics Degree Curriculum
The skills you learn in the computational mathematics degree can be applied to everyday life, from computing security and telecommunication networking to routes for school buses and delivery companies. The degree provides computational mathematics courses such as:
 Calculus
 Differential equations
 Graph theory
 Abstract and linear algebra
 Mathematical modeling
 Numerical analysis
Students are required to complete an experiential learning component of the program, as approved by the School of Mathematics and Statistics. Students are encouraged to participate in research opportunities or cooperative education experiences. You will gain extensive computing skills through a number of highlevel programming, system design, and other computer science courses.
Furthering Your Education in Computational Mathematics
Combined Accelerated Bachelor’s/Master’s Degrees
Today’s careers require advanced degrees grounded in realworld experience. RIT’s Combined Accelerated Bachelor’s/Master’s Degrees enable you to earn both a bachelor’s and a master’s degree in as little as five years of study, all while gaining the valuable handson experience that comes from coops, internships, research, study abroad, and more.
 Computational Mathematics BS/Applied and Computational Mathematics MS: Master the field of computational mathematics with this combined accelerated dual degree. You’ll start by developing a strong foundation in computer science and mathematical analysis with ample opportunity to solidify your knowledge with handson experiences like research, coop, and internships. Moving into the master’s program will deepen your skills with additional coursework along with a thesis or project to apply your knowledge to a field that interests you. Graduates are prepared for indemand computation jobs in industries such as data analytics, engineering, biology, manufacturing, financial planning, and more.
 Computational Mathematics BS/Computer Science MS: Combine a computational mathematics BS degree with a Master’s in computer science to prepare for careers in the rapidly growing and everchanging field of computing. Start by establishing a strong foundation in computing languages, mathematical models, and numerical algorithms that will become the background you need for continued study and application in areas like data management and intelligence systems. You’ll tailor your degree to your interests along the way including selecting a cluster of computer science courses during your graduate work that will help you reach your goals in a career you love.
 +1 MBA: Students who enroll in a qualifying undergraduate degree have the opportunity to add an MBA to their bachelor’s degree after their first year of study, depending on their program. Learn how the +1 MBA can accelerate your learning and position you for success.
Meet us on campus
Learn about academics, coop and internships, financial aid, and more.
Apply for Fall 2025
Early Decision I and Early Action deadlines are November 1.
Careers and Experiential Learning
Typical Job Titles
Data Scientist  Software Engineer  Research Scientist 
Game Designer 
Industries

Insurance

Government (Local, State, Federal)

Internet and Software

Defense

Electronic and Computer Hardware

Manufacturing
Cooperative Education
What’s different about an RIT education? It’s the career experience you gain by completing cooperative education and internships with top companies in every single industry. You’ll earn more than a degree. You’ll gain realworld career experience that sets you apart. It’s exposure–early and often–to a variety of professional work environments, career paths, and industries.
Coops and internships take your knowledge and turn it into knowhow. Science coops include a range of handson experiences, from coops and internships and work in labs to undergraduate research and clinical experience in health care settings. These opportunities provide the handson experience that enables you to apply your scientific, math, and health care knowledge in professional settings while you make valuable connections between classwork and realworld applications.
Although cooperative education is optional for computational mathematics students, it may be used to fulfill the experiential learning component of the program. Students have worked in a variety of settings on problemsolving teams with engineers, biologists, computer scientists, physicists, and marketing specialists.
National Labs Career Events and Recruiting
The Office of Career Services and Cooperative Education offers National Labs and federallyfunded Research Centers from all research areas and sponsoring agencies a variety of options to connect with and recruit students. Students connect with employer partners to gather information on their laboratories and explore coop, internship, research, and fulltime opportunities. These national labs focus on scientific discovery, clean energy development, national security, technology advancements, and more. Recruiting events include our universitywide Fall Career Fair, oncampus and virtual interviews, information sessions, 1:1 networking with lab representatives, and a National Labs Resume Book available to all labs.
Featured Work and Profiles
A Beacon of Public Leadership at RIT Wins Newman Civic Fellowship
Student Nidhi Baindur was awarded a Newman Civic Fellowship for her role as a changemaker and public problemsolver at RIT.
Artificial Intelligence, Mathematics, and Designing Mini Protein Drugs
David Longo ’10 (computational math)
David Longo ’10, CEO of Ordaōs, shares his experience at RIT and explains how computational mathematics allowed him to think outside the box to come up with advanced solutions.
Computational Mathematics and a Future in Cryptography
Keegan Kresge ‘22 (computational mathematics)
Keegan Kresge loves math and programming, making him the perfect fit for cryptography. After completing his degree in computational mathematics, he plans to work at the Department of Defense.
Math + RealWorld Applications = Success
Selene Chew ’16 (computational mathematics)
The computational mathematics program at RIT was the perfect balance of math and computer science for Selene Chew ‘16, who’s now a software engineer at Kensho.
Curriculum for 20242025 for Computational Mathematics BS
Current Students: See Curriculum Requirements
Computational Mathematics, BS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
Choose one of the two sequences:  8  
CSCI141  Computer Science I (General Education) This course serves as an introduction to computational thinking using a problemcentered approach. Specific topics covered include: expression of algorithms in pseudo code and a programming language; functional and imperative programming techniques; control structures; problem solving using recursion; basic searching and sorting; elementary data structures such as lists, trees, and graphs; and correctness, testing and debugging. Assignments (both in class and for homework) requiring a pseudo code solution and an implementation are an integral part of the course. An endofterm project is also required. Lec/Lab 6 (Fall, Spring). 

CSCI142  Computer Science II (General Education) This course delves further into problem solving by continuing the discussion of data structure use and design, but now from an objectoriented perspective. Key topics include more information on tree and graph structures, nested data structures, objects, classes, inheritance, interfaces, objectoriented collection class libraries for abstract data types (e.g. stacks, queues, maps, and trees), and static vs. dynamic data types. Concepts of objectoriented design are a large part of the course. Software qualities related to object orientation, namely cohesion, minimal coupling, modifiability, and extensibility, are all introduced in this course, as well as a few elementary objectoriented design patterns. Input and output streams, graphical user interfaces, and exception handling are covered. Students will also be introduced to a modern integrated software development environment (IDE). Programming projects will be required. (Prerequisites: CSCI141 with a grade of C or better or equivalent course.) Lec/Lab 6 (Fall, Spring, Summer). 

or  
GCIS123  Software Development and Problem Solving I (General Education) A first course introducing students to the fundamentals of computational problem solving. Students will learn a systematic approach to problem solving, including how to frame a problem in computational terms, how to decompose larger problems into smaller components, how to implement innovative software solutions using a contemporary programming language, how to critically debug their solutions, and how to assess the adequacy of the software solution. Additional topics include an introduction to objectoriented programming and data structures such as arrays and stacks. Students will complete both inclass and outofclass assignments. Lab 6 (Fall, Spring). 

GCIS124  Software Development and Problem Solving II (General Education) A second course that delves further into computational problem solving, now with a focus on an objectoriented perspective. There is a continued emphasis on basic software design, testing & verification, and incremental development. Key topics include theoretical abstractions such as classes, objects, encapsulation, inheritance, interfaces, polymorphism, software design comprising multiple classes with UML, data structures (e.g. lists, trees, sets, maps, and graphs), exception/error handling, I/O including files and networking, concurrency, and graphical user interfaces. Additional topics include basic software design principles (coupling, cohesion, information expert, openclosed principle, etc.), test driven development, design patterns, data integrity, and data security. (Prerequisite: C or better in SWEN123 or CSEC123 or GCIS123 or equivalent course.) Lab 6 (Fall, Spring, Summer). 

MATH181  Calculus I (General Education – Mathematical Perspective A) This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH111 or (NMTH220 and NMTH260 or NMTH272 or NMTH275) or equivalent courses with a minimum grade of B, or a score of at least 60% on the RIT Mathematics Placement Exam.) Lecture 4 (Fall, Spring). 
4 
MATH182  Calculus II (General Education – Mathematical Perspective B) This is the second in a twocourse sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C or better in MATH181 or MATH181A or equivalent course.) Lecture 4 (Fall, Spring). 
4 
MATH199  Mathematics and Statistics Seminar This course provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). 
1 
YOPS10  RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). 
0 
General Education – Artistic Perspective 
3  
General Education – Natural Science Inquiry Perspective † 
4  
General Education – Elective 
3  
General Education – FirstYear Writing (WI) 
3  
Second Year  
CSCI243  The Mechanics of Programming Students will be introduced to the details of program structure and the mechanics of execution as well as supportive operating system features. Security and performance issues in program design will be discussed. The program translation process will be examined. Programming assignments will be required. (Prerequisite: C or better in CSCI140 or CSCI142 or CSCI242 or SWEN124 or CSEC124 or GCIS124 or GCIS127 or equivalent course.) Lecture 3 (Fall, Spring, Summer). 
3 
CSCI262  Introduction to Computer Science Theory This course provides an introduction to the theory of computation, including formal languages, grammars, automata theory, computability, and complexity. (Prerequisites: (MATH190 or MATH200) and (CSCI140 or CSCI141 or CSCI242 or SWEN123 or SWEN124 or CSECI123 or CSEC124 or GCIS123 or GCIS124 or GCIS127) or equivalent courses.) Lecture 3 (Fall, Spring, Summer). 
3 
MATH200  Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH182 or equivalent course.) Lecture 3, Recitation 4 (Fall, Spring). 
3 
MATH231  Differential Equations This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms. (Prerequisite: MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH251  Probability and Statistics I This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH173 or MATH182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH399  Mathematical Sciences Job Search Seminar This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). 
0 
Choose one of the following:  4 

MATH221  Multivariable and Vector Calculus (General Education) This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219. (Prerequisite: C or better MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). 

MATH221H  Honors Multivariable and Vector Calculus (General Education) This course is an honors version of MATH221. It includes an introduction to vectors, surfaces, and multivariable functions. It covers limits, partial derivatives and differentiability, multiple integrals, Stokes’ Theorem, Green’s Theorem, the Divergence Theorem, and applications. Unlike MATH221, students in this course will often be expected to learn elementary skills and concepts from their text so that inclass discussion can focus primarily on extending techniques, interpreting results, and exploring mathematical topics in greater depth; homework exercises and projects given in this class will require greater synthesis of concepts and skills, on average, than those in MATH221. Students earning credit for this course cannot earn credit for MATH219 or MATH221. (Prerequisites: C or better in MATH182 or MATH173 or MATH182A and Honors program status or at least a 3.2 cumulative GPA.) Lecture 4 (Fall). 

Choose one of the following:  3 

MATH241  Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH190 or MATH200 or MATH219 or MATH220 or MATH221 or MATH221H or equivalent course.) Lecture 3 (Fall, Spring). 

MATH241H  Honors Linear Algebra This honors course introduces the basic concepts and techniques of linear algebra. Concepts are addressed at a higher level than the standard course in linear algebra, and the topic list is somewhat broader. Topics include linear independence and span, linear functions, solving systems of linear equations using Gaussian elimination, the arithmetic and algebra of matrices, basic properties and interpretation of determinants, vector spaces, the fundamental subspaces of a linear function, eigenvalues and eigenvectors, change of basis, similarity and diagonalization. Students will learn to communicate explanations of mathematical facts and techniques by participating in a collaborative workshop format, and will learn to use MATLAB to solve matrix equations. (Prerequisites: MATH219 or MATH221 or MATH221H or equivalent course and Honors program status or at least a 3.2 cumulative GPA.) Lecture 3 (Spring). 

General Education – Ethical Perspective 
3  
General Education – Global Perspective 
3  
General Education – Scientific Principles Perspective † 
4  
Third Year  
MATH411  Numerical Analysis This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and the solution of initial value problems. (Prerequisites: (MATH231 and (MATH241 or MATH241H)) or MATH233 or equivalent courses.) Lecture 3 (Fall). 
3 
MATH431  Real Variables I This course is an investigation and extension of the theoretical aspects of elementary calculus. Topics include mathematical induction, real numbers, sequences, functions, limits, and continuity. The workshop will focus on helping students develop skill in writing proofs. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH220 or MATH221 or MATH221H or 1016410 or 1016328) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
Program Electives ‡ 
12  
General Education – Social Perspective 
3  
General Education – Immersion 1 
3  
General Education – Elective 
3  
Open Elective 
3  
Fourth Year  
MATH421  Mathematical Modeling (WIPR) This course explores problem solving, formulation of the mathematical model from physical considerations, solution of the mathematical problem, testing the model and interpretation of results. Problems are selected from the physical sciences, engineering, and economics. (Prerequisites: (MATH220 or MATH221 or 1016410 or 1016328) and MATH231 and (MATH241 or MATH241H) and MATH251 or equivalent courses.) Lecture 3 (Fall). 
3 
MATH441  Abstract Algebra I This course covers basic set theory, number theory, groups, subgroups, cyclic and permutation groups, Lagrange and Sylow theorems, quotient groups, and isomorphism theorems. Group Theory finds applications in other scientific disciplines like physics and chemistry. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH241 or MATH241H) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
MATH501  Experiential Learning Requirement in Mathematics The experimental learning requirement in the Applied Mathematics and Computational Mathematics programs can be accomplished in various ways. This course exists to record the completion of experiential learning activities. Such preapproval is considered on a casebycase basis. Lecture (Fall, Spring, Summer). 
0 
Program Electives ‡ 
6  
General Education – Immersion 2, 3 
6  
General Education – Elective 
3  
Open Elective 
9  
Total Semester Credit Hours  122 
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
‡ Three of the program electives must be MATH or STAT courses with course numbers of at least 250, and either Graph Theory (MATH351) or Numerical Linear Algebra (MATH412) must be one of the three courses. One of the program electives must be a CSCI course or SWEN261. One of the program elective courses must be chosen from SWEN261, MATH305, ISTE470, CMPE570, EEEE346, EEEE547, (ISEE301 or MATH301), BIOL235, BIOL470, PHYS377, ENGL581, IGME386, and CSCI courses numbered at least 250.
§ Students are required to complete an experiential learning component of the program: MATH501 Experiential Learning Requirement in Mathematics, as approved by the School of Mathematics and Statistics. Students are urged to fulfill this requirement by participating in research opportunities or coop experiences; students can also fulfill this requirement by taking MATH500 Senior Capstone in Mathematics as a program elective.
Combined Accelerated Bachelor's/Master's Degrees
The curriculum below outlines the typical course sequence(s) for combined accelerated degrees available with this bachelor's degree.
Computational Mathematics, BS degree/Applied and Computational Mathematics (thesis option), MS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
Choose one of the following options:  8 

CSCI141  Computer Science I (General Education) This course serves as an introduction to computational thinking using a problemcentered approach. Specific topics covered include: expression of algorithms in pseudo code and a programming language; functional and imperative programming techniques; control structures; problem solving using recursion; basic searching and sorting; elementary data structures such as lists, trees, and graphs; and correctness, testing and debugging. Assignments (both in class and for homework) requiring a pseudo code solution and an implementation are an integral part of the course. An endofterm project is also required. Lec/Lab 6 (Fall, Spring). 

CSCI142  Computer Science II (General Education) This course delves further into problem solving by continuing the discussion of data structure use and design, but now from an objectoriented perspective. Key topics include more information on tree and graph structures, nested data structures, objects, classes, inheritance, interfaces, objectoriented collection class libraries for abstract data types (e.g. stacks, queues, maps, and trees), and static vs. dynamic data types. Concepts of objectoriented design are a large part of the course. Software qualities related to object orientation, namely cohesion, minimal coupling, modifiability, and extensibility, are all introduced in this course, as well as a few elementary objectoriented design patterns. Input and output streams, graphical user interfaces, and exception handling are covered. Students will also be introduced to a modern integrated software development environment (IDE). Programming projects will be required. (Prerequisites: CSCI141 with a grade of C or better or equivalent course.) Lec/Lab 6 (Fall, Spring, Summer). 

or  
GCIS123  Software Development & Problem Solving I (General Education) A first course introducing students to the fundamentals of computational problem solving. Students will learn a systematic approach to problem solving, including how to frame a problem in computational terms, how to decompose larger problems into smaller components, how to implement innovative software solutions using a contemporary programming language, how to critically debug their solutions, and how to assess the adequacy of the software solution. Additional topics include an introduction to objectoriented programming and data structures such as arrays and stacks. Students will complete both inclass and outofclass assignments. Lab 6 (Fall, Spring). 

GCIS124  Software Development & Problem Solving II (General Education) A second course that delves further into computational problem solving, now with a focus on an objectoriented perspective. There is a continued emphasis on basic software design, testing & verification, and incremental development. Key topics include theoretical abstractions such as classes, objects, encapsulation, inheritance, interfaces, polymorphism, software design comprising multiple classes with UML, data structures (e.g. lists, trees, sets, maps, and graphs), exception/error handling, I/O including files and networking, concurrency, and graphical user interfaces. Additional topics include basic software design principles (coupling, cohesion, information expert, openclosed principle, etc.), test driven development, design patterns, data integrity, and data security. (Prerequisite: C or better in SWEN123 or CSEC123 or GCIS123 or equivalent course.) Lab 6 (Fall, Spring, Summer). 

MATH181  Calculus I (General Education – Mathematical Perspective A) This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH111 or (NMTH220 and NMTH260 or NMTH272 or NMTH275) or equivalent courses with a minimum grade of B, or a score of at least 60% on the RIT Mathematics Placement Exam.) Lecture 4 (Fall, Spring). 
4 
MATH182  Calculus II (General Education – Mathematical Perspective B) This is the second in a twocourse sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C or better in MATH181 or MATH181A or equivalent course.) Lecture 4 (Fall, Spring). 
4 
MATH199  Mathematics and Statistics Seminar This course provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). 
1 
YOPS10  RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). 
0 
General Education – Artistic Perspective 
3  
General Education – Natural Science Inquiry Perspective † 
4  
General Education – Elective 
3  
General Education – FirstYear Writing (WI) 
3  
Open Elective 
3  
Second Year  
CSCI243  The Mechanics of Programming Students will be introduced to the details of program structure and the mechanics of execution as well as supportive operating system features. Security and performance issues in program design will be discussed. The program translation process will be examined. Programming assignments will be required. (Prerequisite: C or better in CSCI140 or CSCI142 or CSCI242 or SWEN124 or CSEC124 or GCIS124 or GCIS127 or equivalent course.) Lecture 3 (Fall, Spring, Summer). 
3 
CSCI262  Introduction to Computer Science Theory This course provides an introduction to the theory of computation, including formal languages, grammars, automata theory, computability, and complexity. (Prerequisites: (MATH190 or MATH200) and (CSCI140 or CSCI141 or CSCI242 or SWEN123 or SWEN124 or CSECI123 or CSEC124 or GCIS123 or GCIS124 or GCIS127) or equivalent courses.) Lecture 3 (Fall, Spring, Summer). 
3 
MATH200  Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH182 or equivalent course.) Lecture 3, Recitation 4 (Fall, Spring). 
3 
MATH231  Differential Equations This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms. (Prerequisite: MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH251  Probability and Statistics I This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH173 or MATH182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH399  Mathematical Sciences Job Search Seminar This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). 
0 
Choose one of the following:  4 

MATH221  Multivariable and Vector Calculus (General Education) This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219. (Prerequisite: C or better MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). 

MATH221H  Honors Multivariable and Vector Calculus (General Education) This course is an honors version of MATH221. It includes an introduction to vectors, surfaces, and multivariable functions. It covers limits, partial derivatives and differentiability, multiple integrals, Stokes’ Theorem, Green’s Theorem, the Divergence Theorem, and applications. Unlike MATH221, students in this course will often be expected to learn elementary skills and concepts from their text so that inclass discussion can focus primarily on extending techniques, interpreting results, and exploring mathematical topics in greater depth; homework exercises and projects given in this class will require greater synthesis of concepts and skills, on average, than those in MATH221. Students earning credit for this course cannot earn credit for MATH219 or MATH221. (Prerequisites: C or better in MATH182 or MATH173 or MATH182A and Honors program status or at least a 3.2 cumulative GPA.) Lecture 4 (Fall). 

Choose one of the following:  3 

MATH241  Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH190 or MATH200 or MATH219 or MATH220 or MATH221 or MATH221H or equivalent course.) Lecture 3 (Fall, Spring). 

MATH241H  Honors Linear Algebra This honors course introduces the basic concepts and techniques of linear algebra. Concepts are addressed at a higher level than the standard course in linear algebra, and the topic list is somewhat broader. Topics include linear independence and span, linear functions, solving systems of linear equations using Gaussian elimination, the arithmetic and algebra of matrices, basic properties and interpretation of determinants, vector spaces, the fundamental subspaces of a linear function, eigenvalues and eigenvectors, change of basis, similarity and diagonalization. Students will learn to communicate explanations of mathematical facts and techniques by participating in a collaborative workshop format, and will learn to use MATLAB to solve matrix equations. (Prerequisites: MATH219 or MATH221 or MATH221H or equivalent course and Honors program status or at least a 3.2 cumulative GPA.) Lecture 3 (Spring). 

General Education – Ethical Perspective 
3  
General Education – Global Perspective 
3  
General Education – Scientific Principles Perspective † 
4  
Third Year  
MATH431  Real Variables I This course is an investigation and extension of the theoretical aspects of elementary calculus. Topics include mathematical induction, real numbers, sequences, functions, limits, and continuity. The workshop will focus on helping students develop skill in writing proofs. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH220 or MATH221 or MATH221H or 1016410 or 1016328) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
MATH441  Abstract Algebra I This course covers basic set theory, number theory, groups, subgroups, cyclic and permutation groups, Lagrange and Sylow theorems, quotient groups, and isomorphism theorems. Group Theory finds applications in other scientific disciplines like physics and chemistry. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH241 or MATH241H) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
Program Electives ‡ 
12  
General Education – Social Perspective 
3  
General Education – Immersion 1, 2 
6  
General Education – Elective 
3  
Fourth Year  
MATH421  Mathematical Modeling (WIPR) This course explores problem solving, formulation of the mathematical model from physical considerations, solution of the mathematical problem, testing the model and interpretation of results. Problems are selected from the physical sciences, engineering, and economics. (Prerequisites: (MATH220 or MATH221 or 1016410 or 1016328) and MATH231 and (MATH241 or MATH241H) and MATH251 or equivalent courses.) Lecture 3 (Fall). 
3 
MATH501  Experiential Learning Requirement in Mathematics The experimental learning requirement in the Applied Mathematics and Computational Mathematics programs can be accomplished in various ways. This course exists to record the completion of experiential learning activities. Such preapproval is considered on a casebycase basis. Lecture (Fall, Spring, Summer). 
0 
MATH602  Numerical Analysis I This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and matrix algebra. (Prerequisites: MATH411 or equivalent course and graduate standing.) Lecture 3 (Fall). 
3 
MATH606  Graduate Seminar I The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics. (This course is restricted to students in the ACMTHMS or MATHMLPHD programs.) Lecture 2 (Fall). 
1 
MATH607  Graduate Seminar II This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics. (Prerequisite: MATH606 or equivalent course or students in the ACMTHMS or MATHMLPHD programs.) Lecture 2 (Spring). 
1 
Math Graduate Core Courses 
6  
Open Electives 
9  
General Education – Immersion 3 
3  
General Education – Elective 
3  
Program Elective ‡ 
3  
Fifth Year  
MATH790  Research & Thesis Masterslevel research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course is restricted to students in the ACMTHMS or MATHMLPHD programs.) Thesis (Fall, Spring, Summer). 
7 
MATH Graduate Electives 
12  
Total Semester Credit Hours  146 
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
*Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
‡ Three of the program electives must be MATH or STAT courses with course numbers of at least 250, and either Graph Theory (MATH351) or Numerical Linear Algebra (MATH412) must be one of the three courses. One of the program electives must be a CSCI course or SWEN261. One of the program elective courses must be chosen from SWEN261, MATH305, ISTE470, CMPE570, EEEE346, EEEE547, (ISEE301 or MATH301), BIOL235, BIOL470, PHYS377, ENGL581, IGME386, and CSCI courses numbered at least 250.
§ Students are required to complete an experiential learning component of the program: MATH501 Experiential Learning Requirement in Mathematics, as approved by the School of Mathematics and Statistics. Students are urged to fulfill this requirement by participating in research opportunities or coop experiences; students can also fulfill this requirement by taking MATH500 Senior Capstone in Mathematics as a program elective.
Computational Mathematics, BS degree/Applied and Computational Mathematics (project option), MS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
Choose one of the following sequences:  8 

CSCI141  Computer Science I (General Education – Elective) This course serves as an introduction to computational thinking using a problemcentered approach. Specific topics covered include: expression of algorithms in pseudo code and a programming language; functional and imperative programming techniques; control structures; problem solving using recursion; basic searching and sorting; elementary data structures such as lists, trees, and graphs; and correctness, testing and debugging. Assignments (both in class and for homework) requiring a pseudo code solution and an implementation are an integral part of the course. An endofterm project is also required. Lec/Lab 6 (Fall, Spring). 

CSCI142  Computer Science II (General Education – Elective) This course delves further into problem solving by continuing the discussion of data structure use and design, but now from an objectoriented perspective. Key topics include more information on tree and graph structures, nested data structures, objects, classes, inheritance, interfaces, objectoriented collection class libraries for abstract data types (e.g. stacks, queues, maps, and trees), and static vs. dynamic data types. Concepts of objectoriented design are a large part of the course. Software qualities related to object orientation, namely cohesion, minimal coupling, modifiability, and extensibility, are all introduced in this course, as well as a few elementary objectoriented design patterns. Input and output streams, graphical user interfaces, and exception handling are covered. Students will also be introduced to a modern integrated software development environment (IDE). Programming projects will be required. (Prerequisites: CSCI141 with a grade of C or better or equivalent course.) Lec/Lab 6 (Fall, Spring, Summer). 

or  
GCIS123  Software Development & Problem Solving I (General Education) A first course introducing students to the fundamentals of computational problem solving. Students will learn a systematic approach to problem solving, including how to frame a problem in computational terms, how to decompose larger problems into smaller components, how to implement innovative software solutions using a contemporary programming language, how to critically debug their solutions, and how to assess the adequacy of the software solution. Additional topics include an introduction to objectoriented programming and data structures such as arrays and stacks. Students will complete both inclass and outofclass assignments. Lab 6 (Fall, Spring). 

GCIS124  Software Development & Problem Solving II (General Education) A second course that delves further into computational problem solving, now with a focus on an objectoriented perspective. There is a continued emphasis on basic software design, testing & verification, and incremental development. Key topics include theoretical abstractions such as classes, objects, encapsulation, inheritance, interfaces, polymorphism, software design comprising multiple classes with UML, data structures (e.g. lists, trees, sets, maps, and graphs), exception/error handling, I/O including files and networking, concurrency, and graphical user interfaces. Additional topics include basic software design principles (coupling, cohesion, information expert, openclosed principle, etc.), test driven development, design patterns, data integrity, and data security. (Prerequisite: C or better in SWEN123 or CSEC123 or GCIS123 or equivalent course.) Lab 6 (Fall, Spring, Summer). 

MATH181  Calculus I (General Education – Mathematical Perspective A) This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH111 or (NMTH220 and NMTH260 or NMTH272 or NMTH275) or equivalent courses with a minimum grade of B, or a score of at least 60% on the RIT Mathematics Placement Exam.) Lecture 4 (Fall, Spring). 
4 
MATH182  Calculus II (General Education – Mathematical Perspective B) This is the second in a twocourse sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C or better in MATH181 or MATH181A or equivalent course.) Lecture 4 (Fall, Spring). 
4 
MATH199  Mathematics and Statistics Seminar This course provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). 
1 
YOPS10  RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). 
0 
General Education – Artistic Perspective 
3  
General Education – Natural Science Inquiry Perspective† 
4  
General Education – Elective 
3  
General Education – FirstYear Writing (WI) 
3  
Open Elective 
3  
Second Year  
CSCI243  The Mechanics of Programming Students will be introduced to the details of program structure and the mechanics of execution as well as supportive operating system features. Security and performance issues in program design will be discussed. The program translation process will be examined. Programming assignments will be required. (Prerequisite: C or better in CSCI140 or CSCI142 or CSCI242 or SWEN124 or CSEC124 or GCIS124 or GCIS127 or equivalent course.) Lecture 3 (Fall, Spring, Summer). 
3 
CSCI262  Introduction to Computer Science Theory This course provides an introduction to the theory of computation, including formal languages, grammars, automata theory, computability, and complexity. (Prerequisites: (MATH190 or MATH200) and (CSCI140 or CSCI141 or CSCI242 or SWEN123 or SWEN124 or CSECI123 or CSEC124 or GCIS123 or GCIS124 or GCIS127) or equivalent courses.) Lecture 3 (Fall, Spring, Summer). 
3 
MATH200  Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH182 or equivalent course.) Lecture 3, Recitation 4 (Fall, Spring). 
3 
MATH231  Differential Equations This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms. (Prerequisite: MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH251  Probability and Statistics I This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH173 or MATH182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH399  Mathematical Sciences Job Search Seminar This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). 
0 
Choose one of the following:  4 

MATH221  Multivariable and Vector Calculus (General Education) This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219. (Prerequisite: C or better MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). 

MATH221H  Honors Multivariable and Vector Calculus (General Education) This course is an honors version of MATH221. It includes an introduction to vectors, surfaces, and multivariable functions. It covers limits, partial derivatives and differentiability, multiple integrals, Stokes’ Theorem, Green’s Theorem, the Divergence Theorem, and applications. Unlike MATH221, students in this course will often be expected to learn elementary skills and concepts from their text so that inclass discussion can focus primarily on extending techniques, interpreting results, and exploring mathematical topics in greater depth; homework exercises and projects given in this class will require greater synthesis of concepts and skills, on average, than those in MATH221. Students earning credit for this course cannot earn credit for MATH219 or MATH221. (Prerequisites: C or better in MATH182 or MATH173 or MATH182A and Honors program status or at least a 3.2 cumulative GPA.) Lecture 4 (Fall). 

Choose one of the following:  3 

MATH241  Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH190 or MATH200 or MATH219 or MATH220 or MATH221 or MATH221H or equivalent course.) Lecture 3 (Fall, Spring). 

MATH241H  Honors Linear Algebra This honors course introduces the basic concepts and techniques of linear algebra. Concepts are addressed at a higher level than the standard course in linear algebra, and the topic list is somewhat broader. Topics include linear independence and span, linear functions, solving systems of linear equations using Gaussian elimination, the arithmetic and algebra of matrices, basic properties and interpretation of determinants, vector spaces, the fundamental subspaces of a linear function, eigenvalues and eigenvectors, change of basis, similarity and diagonalization. Students will learn to communicate explanations of mathematical facts and techniques by participating in a collaborative workshop format, and will learn to use MATLAB to solve matrix equations. (Prerequisites: MATH219 or MATH221 or MATH221H or equivalent course and Honors program status or at least a 3.2 cumulative GPA.) Lecture 3 (Spring). 

General Education – Ethical Perspective 
3  
General Education – Global Perspective 
3  
General Education – Scientific Principles Perspective† 
4  
Third Year  
MATH431  Real Variables I This course is an investigation and extension of the theoretical aspects of elementary calculus. Topics include mathematical induction, real numbers, sequences, functions, limits, and continuity. The workshop will focus on helping students develop skill in writing proofs. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH220 or MATH221 or MATH221H or 1016410 or 1016328) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
MATH441  Abstract Algebra I This course covers basic set theory, number theory, groups, subgroups, cyclic and permutation groups, Lagrange and Sylow theorems, quotient groups, and isomorphism theorems. Group Theory finds applications in other scientific disciplines like physics and chemistry. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH241 or MATH241H) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
Program Electives ‡ 
12  
General Education – Social Perspective 
3  
General Education – Immersion 1, 2 
6  
General Education – Elective 
3  
Fourth Year  
MATH421  Mathematical Modeling (WIPR) This course explores problem solving, formulation of the mathematical model from physical considerations, solution of the mathematical problem, testing the model and interpretation of results. Problems are selected from the physical sciences, engineering, and economics. (Prerequisites: (MATH220 or MATH221 or 1016410 or 1016328) and MATH231 and (MATH241 or MATH241H) and MATH251 or equivalent courses.) Lecture 3 (Fall). 
3 
MATH501  Experiential Learning Requirement in Mathematics The experimental learning requirement in the Applied Mathematics and Computational Mathematics programs can be accomplished in various ways. This course exists to record the completion of experiential learning activities. Such preapproval is considered on a casebycase basis. Lecture (Fall, Spring, Summer). 
0 
MATH602  Numerical Analysis I This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and matrix algebra. (Prerequisites: MATH411 or equivalent course and graduate standing.) Lecture 3 (Fall). 
3 
MATH606  Graduate Seminar I The course prepares students to engage in activities necessary for independent mathematical research and introduces students to a broad range of active interdisciplinary programs related to applied mathematics. (This course is restricted to students in the ACMTHMS or MATHMLPHD programs.) Lecture 2 (Fall). 
1 
MATH607  Graduate Seminar II This course is a continuation of Graduate Seminar I. It prepares students to engage in activities necessary for independent mathematical research and introduces them to a broad range of active interdisciplinary programs related to applied mathematics. (Prerequisite: MATH606 or equivalent course or students in the ACMTHMS or MATHMLPHD programs.) Lecture 2 (Spring). 
1 
Math Graduate Core Courses 
6  
Open Electives 
9  
General Education – Immersion 3 
3  
General Education – Elective 
3  
Program Elective ‡ 
3  
Fifth Year  
MATH790  Research & Thesis Masterslevel research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course is restricted to students in the ACMTHMS or MATHMLPHD programs.) Thesis (Fall, Spring, Summer). 
4 
MATH Graduate Electives 
15  
Total Semester Credit Hours  146 
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
‡ Three of the program electives must be MATH or STAT courses with course numbers of at least 250, and either Graph Theory (MATH351) or Numerical Linear Algebra (MATH412) must be one of the three courses. One of the program electives must be a CSCI course or SWEN261. One of the program elective courses must be chosen from SWEN261, MATH305, ISTE470, CMPE570, EEEE346, EEEE547, (ISEE301 or MATH301), BIOL235, BIOL470, PHYS377, ENGL581, IGME386, and CSCI courses numbered at least 250.
§ Students are required to complete an experiential learning component of the program: MATH501 Experiential Learning Requirement in Mathematics, as approved by the School of Mathematics and Statistics. Students are urged to fulfill this requirement by participating in research opportunities or coop experiences; students can also fulfill this requirement by taking MATH500 Senior Capstone in Mathematics as a program elective.
Computational Mathematics, BS degree/Computer Science, MS degree, typical course sequence
Course  Sem. Cr. Hrs.  

First Year  
Choose one of the following sequences:  8 

CSCI141  Computer Science I (General Education) This course serves as an introduction to computational thinking using a problemcentered approach. Specific topics covered include: expression of algorithms in pseudo code and a programming language; functional and imperative programming techniques; control structures; problem solving using recursion; basic searching and sorting; elementary data structures such as lists, trees, and graphs; and correctness, testing and debugging. Assignments (both in class and for homework) requiring a pseudo code solution and an implementation are an integral part of the course. An endofterm project is also required. Lec/Lab 6 (Fall, Spring). 

CSCI142  Computer Science II (General Education) This course delves further into problem solving by continuing the discussion of data structure use and design, but now from an objectoriented perspective. Key topics include more information on tree and graph structures, nested data structures, objects, classes, inheritance, interfaces, objectoriented collection class libraries for abstract data types (e.g. stacks, queues, maps, and trees), and static vs. dynamic data types. Concepts of objectoriented design are a large part of the course. Software qualities related to object orientation, namely cohesion, minimal coupling, modifiability, and extensibility, are all introduced in this course, as well as a few elementary objectoriented design patterns. Input and output streams, graphical user interfaces, and exception handling are covered. Students will also be introduced to a modern integrated software development environment (IDE). Programming projects will be required. (Prerequisites: CSCI141 with a grade of C or better or equivalent course.) Lec/Lab 6 (Fall, Spring, Summer). 

or  
GCIS123  Software Development & Problem Solving I (General Education) A first course introducing students to the fundamentals of computational problem solving. Students will learn a systematic approach to problem solving, including how to frame a problem in computational terms, how to decompose larger problems into smaller components, how to implement innovative software solutions using a contemporary programming language, how to critically debug their solutions, and how to assess the adequacy of the software solution. Additional topics include an introduction to objectoriented programming and data structures such as arrays and stacks. Students will complete both inclass and outofclass assignments. Lab 6 (Fall, Spring). 

GCIS124  Software Development & Problem Solving II (General Education) A second course that delves further into computational problem solving, now with a focus on an objectoriented perspective. There is a continued emphasis on basic software design, testing & verification, and incremental development. Key topics include theoretical abstractions such as classes, objects, encapsulation, inheritance, interfaces, polymorphism, software design comprising multiple classes with UML, data structures (e.g. lists, trees, sets, maps, and graphs), exception/error handling, I/O including files and networking, concurrency, and graphical user interfaces. Additional topics include basic software design principles (coupling, cohesion, information expert, openclosed principle, etc.), test driven development, design patterns, data integrity, and data security. (Prerequisite: C or better in SWEN123 or CSEC123 or GCIS123 or equivalent course.) Lab 6 (Fall, Spring, Summer). 

MATH181  Calculus I (General Education – Mathematical Perspective A) This is the first in a twocourse sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH111 or (NMTH220 and NMTH260 or NMTH272 or NMTH275) or equivalent courses with a minimum grade of B, or a score of at least 60% on the RIT Mathematics Placement Exam.) Lecture 4 (Fall, Spring). 
4 
MATH182  Calculus II (General Education – Mathematical Perspective B) This is the second in a twocourse sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C or better in MATH181 or MATH181A or equivalent course.) Lecture 4 (Fall, Spring). 
4 
MATH199  Mathematics and Statistics Seminar This course provides an introduction to math and statistics software. The course provides practice in technical writing. Seminar 1 (Fall). 
1 
YOPS10  RIT 365: RIT Connections RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their firstyear experiences, receive feedback, and develop a personal plan for future action in order to develop foundational selfawareness and recognize broadbased professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring). 
0 
General Education – Artistic Perspective 
3  
General Education – Natural Science Inquiry Perspective† 
4  
General Education – Elective 
3  
General Education – FirstYear Writing (WI) 
3  
Second Year  
CSCI243  The Mechanics of Programming Students will be introduced to the details of program structure and the mechanics of execution as well as supportive operating system features. Security and performance issues in program design will be discussed. The program translation process will be examined. Programming assignments will be required. (Prerequisite: C or better in CSCI140 or CSCI142 or CSCI242 or SWEN124 or CSEC124 or GCIS124 or GCIS127 or equivalent course.) Lecture 3 (Fall, Spring, Summer). 
3 
CSCI262  Introduction to Computer Science Theory This course provides an introduction to the theory of computation, including formal languages, grammars, automata theory, computability, and complexity. (Prerequisites: (MATH190 or MATH200) and (CSCI140 or CSCI141 or CSCI242 or SWEN123 or SWEN124 or CSECI123 or CSEC124 or GCIS123 or GCIS124 or GCIS127) or equivalent courses.) Lecture 3 (Fall, Spring, Summer). 
3 
MATH200  Discrete Mathematics and Introduction to Proofs This course prepares students for professions that use mathematics in daily practice, and for mathematics courses beyond the introductory level where it is essential to communicate effectively in the language of mathematics. It covers various methods of mathematical proof, starting with basic techniques in propositional and predicate calculus and set theory, and then moving to applications in advanced mathematics. (Prerequisite: MATH182 or equivalent course.) Lecture 3, Recitation 4 (Fall, Spring). 
3 
MATH231  Differential Equations This course is an introduction to the study of ordinary differential equations and their applications. Topics include solutions to first order equations and linear second order equations, method of undetermined coefficients, variation of parameters, linear independence and the Wronskian, vibrating systems, and Laplace transforms. (Prerequisite: MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH251  Probability and Statistics This course introduces sample spaces and events, axioms of probability, counting techniques, conditional probability and independence, distributions of discrete and continuous random variables, joint distributions (discrete and continuous), the central limit theorem, descriptive statistics, interval estimation, and applications of probability and statistics to realworld problems. A statistical package such as Minitab or R is used for data analysis and statistical applications. (Prerequisites: MATH173 or MATH182 or MATH 182A or equivalent course.) Lecture 3, Recitation 1 (Fall, Spring, Summer). 
3 
MATH399  Mathematical Sciences Job Search Seminar This course helps students prepare to search for coop or fulltime employment. Students will learn strategies for conducting a successful job search and transitioning into the work world. The course meets one hour each week for five weeks. Lecture 1 (Fall, Spring). 
0 
Choose one of the following:  4 

MATH221  Multivariable and Vector Calculus (General Education) This course is principally a study of the calculus of functions of two or more variables, but also includes a study of vectors, vectorvalued functions and their derivatives. The course covers limits, partial derivatives, multiple integrals, Stokes' Theorem, Green's Theorem, the Divergence Theorem, and applications in physics. Credit cannot be granted for both this course and MATH219. (Prerequisite: C or better MATH173 or MATH182 or MATH182A or equivalent course.) Lecture 4 (Fall, Spring, Summer). 

MATH221H  Honors Multivariable and Vector Calculus (General Education) This course is an honors version of MATH221. It includes an introduction to vectors, surfaces, and multivariable functions. It covers limits, partial derivatives and differentiability, multiple integrals, Stokes’ Theorem, Green’s Theorem, the Divergence Theorem, and applications. Unlike MATH221, students in this course will often be expected to learn elementary skills and concepts from their text so that inclass discussion can focus primarily on extending techniques, interpreting results, and exploring mathematical topics in greater depth; homework exercises and projects given in this class will require greater synthesis of concepts and skills, on average, than those in MATH221. Students earning credit for this course cannot earn credit for MATH219 or MATH221. (Prerequisites: C or better in MATH182 or MATH173 or MATH182A and Honors program status or at least a 3.2 cumulative GPA.) Lecture 4 (Fall). 

Choose one of the following:  3 

MATH241  Linear Algebra This course is an introduction to the basic concepts of linear algebra, and techniques of matrix manipulation. Topics include linear transformations, Gaussian elimination, matrix arithmetic, determinants, vector spaces, linear independence, basis, null space, row space, and column space of a matrix, eigenvalues, eigenvectors, change of basis, similarity and diagonalization. Various applications are studied throughout the course. (Prerequisites: MATH190 or MATH200 or MATH219 or MATH220 or MATH221 or MATH221H or equivalent course.) Lecture 3 (Fall, Spring). 

MATH241H  Honors Linear Algebra This honors course introduces the basic concepts and techniques of linear algebra. Concepts are addressed at a higher level than the standard course in linear algebra, and the topic list is somewhat broader. Topics include linear independence and span, linear functions, solving systems of linear equations using Gaussian elimination, the arithmetic and algebra of matrices, basic properties and interpretation of determinants, vector spaces, the fundamental subspaces of a linear function, eigenvalues and eigenvectors, change of basis, similarity and diagonalization. Students will learn to communicate explanations of mathematical facts and techniques by participating in a collaborative workshop format, and will learn to use MATLAB to solve matrix equations. (Prerequisites: MATH219 or MATH221 or MATH221H or equivalent course and Honors program status or at least a 3.2 cumulative GPA.) Lecture 3 (Spring). 

General Education – Ethical Perspective 
3  
General Education – Global Perspective 
3  
General Education – Scientific Principles Perspective† 
4  
Third Year  
MATH411  Numerical Analysis This course covers numerical techniques for the solution of nonlinear equations, interpolation, differentiation, integration, and the solution of initial value problems. (Prerequisites: (MATH231 and (MATH241 or MATH241H)) or MATH233 or equivalent courses.) Lecture 3 (Fall). 
3 
MATH431  Real Variables I This course is an investigation and extension of the theoretical aspects of elementary calculus. Topics include mathematical induction, real numbers, sequences, functions, limits, and continuity. The workshop will focus on helping students develop skill in writing proofs. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH220 or MATH221 or MATH221H or 1016410 or 1016328) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
Program Electives ‡ 
12  
General Education – Social Perspective 
3  
General Education – Immersion 1 
3  
General Education – Elective 
3  
Open Elective 
3  
Fourth Year  
CSCI664  Computational Complexity This course provides an introduction to computational complexity theory. It covers the P=NP problem, time and space complexity, randomization, approximability, and relativization. (Prerequisites: (CSCI661 or CSCI660 or CSCI262 or CSCI263) and (CSCI665 or CSCI261 or CSCI264) or equivalent courses.) Lecture 3 (Spring). 
3 
CSCI665  Foundations of Algorithms This course provides an introduction to the design and analysis of algorithms. It covers a variety of classical algorithms and their complexity and will equip students with the intellectual tools to design, analyze, implement, and evaluate their own algorithms. Note: students who take CSCI261 or CSCI264 may not take CSCI665 for credit. (Prerequisites: (CSCI603 and CSCI605 and CSCI661 with grades of B or better) or ((CSCI243 or SWEN262) and (CSCI262 or CSCI263)) or equivalent courses. This course is restricted to COMPSCIMS, COMPSCIBS/MS, or COMPISPHD students.) Lec/Lab 3 (Fall, Spring). 
3 
MATH421  Mathematical Modeling (WIPR) This course explores problem solving, formulation of the mathematical model from physical considerations, solution of the mathematical problem, testing the model and interpretation of results. Problems are selected from the physical sciences, engineering, and economics. (Prerequisites: (MATH220 or MATH221 or 1016410 or 1016328) and MATH231 and (MATH241 or MATH241H) and MATH251 or equivalent courses.) Lecture 3 (Fall). 
3 
MATH441  Abstract Algebra I This course covers basic set theory, number theory, groups, subgroups, cyclic and permutation groups, Lagrange and Sylow theorems, quotient groups, and isomorphism theorems. Group Theory finds applications in other scientific disciplines like physics and chemistry. (Prerequisites: (MATH190 or MATH200 or 1055265) and (MATH241 or MATH241H) or equivalent courses.) Lec/Lab 4 (Fall, Spring). 
3 
MATH501  Experiential Learning Requirement in Mathematics The experimental learning requirement in the Applied Mathematics and Computational Mathematics programs can be accomplished in various ways. This course exists to record the completion of experiential learning activities. Such preapproval is considered on a casebycase basis. Lecture (Fall, Spring, Summer). 
0 
Program Elective ‡ 
3  
Open Electives 
6  
General Education – Immersion 2, 3 
6  
General Education – Elective 
3  
Fifth Year  
CSCI610  Foundations of Computer Graphics Foundations of Computer Graphics is a study of the hardware and software principles of interactive raster graphics. Topics include an introduction to the basic concepts, 2D and 3D modeling and transformations, viewing transformations, projections, rendering techniques, graphical software packages and graphics systems. The course will focus on rasterization techniques and emphasize the hardware rasterization pipeline including the use of hardware shaders. Students will use a standard computer graphics API to reinforce concepts and study fundamental computer graphics algorithms. Programming projects and a survey of the current graphics literature will be required. Note: students who complete CSCI510 may not take CSCI610 for credit. (Prerequisite: (CSCI603 or CSCI605 with a grade of B or better) or (CSCI243 or SWEN262). May not take and receive credit for CSCI610 and CSCI510. If earned credit for/or currently enrolled in CSCI510 you will not be permitted to enroll in CSCI610.) Lecture 3 (Fall, Spring). 
3 
CSCI790  Computer Science MS Thesis Thesis capstone of the master's degree program. Student must submit an acceptable thesis proposal in order to enroll. It is expected that the work would lead to a paper of the caliber of those generally acceptable to a national conference. (Enrollment in this course requires permission from the department offering the course.) Thesis (Fall, Spring, Summer). 
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CSCI799  Computer Science Graduate Independent Study Students work with a supervising faculty member on topics of mutual interest. A student works with a potential faculty sponsor to draft a proposal that describes what a student plans to do, what deliverables are expected, how the student's work will be evaluated, and how much credit will be assigned for successful completion of the work. The faculty sponsor proposes the grade, but before the grade is officially recorded, the student must submit a final report that summarizes what was actually accomplished. (Enrollment in this course requires permission from the department offering the course.) Ind Study (Fall, Spring, Summer). 
6 
CSCI Cluster Courses 
9  
Total Semester Credit Hours  146 
Please see General Education Curriculum (GE) for more information.
(WI) Refers to a writing intensive course within the major.
* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.
† Students will satisfy this requirement by taking either University Physics I (PHYS211) and University Physics II (PHYS212) or General & Analytical Chemistry I and Lab (CHMG141/145) and General & Analytical Chemistry II and Lab (CHMG142/146) or General Biology I and Lab (BIOL101/103) and General Biology II and Lab (BIOL102/104).
‡ Three of the program electives must be MATH or STAT courses with course numbers of at least 250, and either Graph Theory (MATH351) or Numerical Linear Algebra (MATH412) must be one of the three courses. One of the program electives must be a CSCI course or SWEN261. One of the program elective courses must be chosen from SWEN261, MATH305, ISTE470, CMPE570, EEEE346, EEEE547, (ISEE301 or MATH301), BIOL235, BIOL470, PHYS377, ENGL581, IGME386, and CSCI courses numbered at least 250.
§ Students are required to complete an experiential learning component of the program: MATH501 Experiential Learning Requirement in Mathematics, as approved by the School of Mathematics and Statistics. Students are urged to fulfill this requirement by participating in research opportunities or coop experiences; students can also fulfill this requirement by taking MATH500 Senior Capstone in Mathematics as a program elective.
Admissions and Financial Aid
This program is STEM designated when studying on campus and full time.
FirstYear Admission
A strong performance in a college preparatory program is expected. This includes:
 4 years of English
 3 years of social studies and/or history
 4 years of mathematics is required and must include algebra, geometry, algebra 2/trigonometry, and precalculus. Calculus is preferred.
 23 years of science is required and must include chemistry or physics; both are recommended.
Transfer Admission
Transfer course recommendations without associate degree
Courses in liberal arts, physics, math, and chemistry
Appropriate associate degree programs for transfer
AS degree in liberal arts with math/science option
Financial Aid and Scholarships
100% of all incoming firstyear and transfer students receive aid.
RIT’s personalized and comprehensive financial aid program includes scholarships, grants, loans, and campus employment programs. When all these are put to work, your actual cost may be much lower than the published estimated cost of attendance.
Learn more about financial aid and scholarships
Research
Undergraduate Research Opportunities
Many students join research teams and engage in research projects starting as early as their first year. Participation in undergraduate research leads to the development of realworld skills, enhanced problemsolving techniques, and broader career opportunities. Our students have opportunities to travel to national conferences for presentations and also become contributing authors on peerreviewed manuscripts. Explore the variety of mathematics and statistics undergraduate research projects happening across the university.
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The Rochester Beacon features Nikolas Kelly '20 (supply chain management), cofounder and chief product officer of SignSpeak, and Nicholas Wilkins '19 (computational mathematics), '19 MS (computer science).
Contact
School of Mathematics and Statistics