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Moravian University
Catalog

Mathematics and Computer Science

Chair: Professor Shank
Professor: Coleman, Fraboni, Schultheis
Associate Professors:  Hartshorn, Talbott
Assistant Professor: Bush, Curley
Visiting Associate Professor: Schaper
Instructor of Mathematics: Nataro, Ward

Computer Science (CSCI) Course Descriptions

Mathematics (MATH) Course Descriptions 

Mathematics:  

Mission: The Mathematics program at Moravian University fosters a community of faculty and students who promote the aesthetic, theoretic, and pragmatic qualities of mathematics in order to develop in its students communication and problem solving skills applicable to many disciplines that prepare them for fulfilling careers.

The Mathematics and Computer Science department offers three tracks for students in Pure Mathematics, Applied Mathematics, or Actuarial Science.  Study in this department ensures you'll gain valuable skills that will help you throughout your work life. You'll learn how to problem-solve and how to approach mathematics as a tool while gaining an in-depth knowledge of software and systems concepts in computer science, learning where they may fit in the quickly growing field of technology.

Pure Mathematics Track: Student interested in a broad mathematics background or students who plan to attend graduate school in mathematics should consider the Pure Mathematics Track.  The Pure Mathematics track also provides quantitative and analytical skills, which prepare students to enter the workforce after graduation. Early, Middle, and Secondary education students are encouraged to follow the Pure Mathematics Track.

Applied Mathematics Track: Students interested in working in business or industry or students who plan to attend graduate school in applied mathematics should consider the Applied Mathematics Track.  The Applied Mathematics Track provides a strong foundation of mathematics and the tools required to solve real-world problems.

Actuarial Science Track: Students interested in becoming an actuary should follow the Actuarial Science Track. An actuary is a mathematician trained to analyze information to calculate the monetary value of risk.  Actuaries progress in their professional career by passing a series of actuarial exams. The Actuarial Science Track prepares students for the first two actuarial exams (EXAM P and FM), giving them a solid foundation to begin a career as an actuary.  

The Major in Mathematics

The Mathematics program consists of three distinct tracks: Pure Mathematics, Applied Mathematics, and Actuarial Science.  All mathematics majors are required to select a track when declaring their major.

All three tracks require the following four courses:  MATH 170 (or its equivalent sequence MATH 106 and MATH 166), MATH 171, 211, and 212.   In addition, all three tracks require a capstone experience. MATH 370 will serve as the capstone experience for most majors. Successful completion of MATH 400-401 (Honors) can serve as an alternative capstone experience, although students who plan to pursue an Honors project are encouraged to take MATH 370 in their junior year.  In addition, students must have at least three courses numbered 310-384, 390-399, or 400-401. (One of these three may be MATH 370.)

In order that students may understand and experience the depth and breadth of mathematics, the department’s major courses (other than the required courses and MATH 370) have been grouped into two areas: pure mathematics courses and applied mathematics courses.  

Current catalog courses in each of these areas are as follows:

Pure Mathematics Courses: MATH 220, 245, 324, 345, 347, 348, 365, and 366.
Applied Mathematics Courses:  MATH 230, 231, 251, 254, 255, 258, 337, 355, and PHYS 343.
As special topics or new courses are offered, they will be placed in the appropriate group.

Pure Mathematics Track:
In addition to the four required courses and the capstone experience, the Pure Mathematics Track requires five additional courses in Mathematics.  One of these courses is a required course, MATH 220. For the remaining four courses, students in this track will choose three Pure Mathematics Courses and one Applied Mathematics Course.  
Students in the Pure Mathematics track must also choose two co-requisite courses from the following group of four courses: PHYS 111, PHYS 112, CSCI 120 and CSCI 121. Substitutions for this requirement may be made only with the approval of the Mathematics and Computer Science Department.

Applied Mathematics Track:  
In addition to the four required courses and the capstone experience, the Applied Mathematics Track requires six additional courses in Mathematics.  Two of these courses are required courses, MATH 220 and 254. For the remaining four courses, students in this track will choose three Applied Mathematics Courses and one Pure Mathematics Course.  

Applied Mathematics students must also choose two co-requisite courses from the following group of four courses: PHYS 111, PHYS 112, CSCI 120 and CSCI 121. Substitutions for this requirement may be made only with the approval of the Mathematics and Computer Science Department.

Actuarial Science Track:  
In addition to the four required courses and the capstone experience, the Actuarial Science Track requires six additional courses in Mathematics; three required courses and three electives numbered 210 or higher.  The additional required courses are MATH 231, 332 and 251. The three additional electives must include at least one Applied Mathematics Course and at least one Pure Mathematics Course.

Actuarial Science students must also take three co-requisite courses, which includes CSCI 120, ECON 152, and one ECON course chosen from the following group of three courses: ECON 225, 226 and 256.  Substitutions for this requirement may be made only with the approval of the Mathematics and Computer Science Department.

Secondary Education Certification:
Students planning to teach mathematics in secondary schools who are interested in the Pure Mathematics Track must complete the following courses: MATH 170 (or its equivalent sequence MATH 106 and  MATH 166), 171, 211, 212, 220, 231, 347, 348, 370, and one of the following: MATH 324, 365, or 366.

Students planning to teach mathematics in secondary schools who are interested in the Applied Mathematics Track must complete the following courses: MATH 170 (or its equivalent sequence MATH 106 and MATH 166), 171, 211, 212, 220, 231, 254, 347, 348, 370, and one of the following: MATH 230, 258, 251, 337, or PHYS 343.

Middle Level  Education Certification:
Students who are seeking certification in middle level education with a major in mathematics can complete either the Pure or Applied Mathematics Track.

Early Childhood Education Certification:
Students who are seeking certification in early childhood education with a major in mathematics should take the Pure Mathematics Track and are required to complete PHYS 111. The second co-requisite course is waived for these students. Students who are pursuing early childhood teacher certification with a major in mathematics do not need to complete MATH 120.

Courses in Mathematics (MATH) are listed below.

The Minor in Mathematics

The minor in mathematics consists of five course units in mathematics: MATH 170 (or the equivalent sequence Mathematics MATH 106 and MATH 166), MATH 171, and three MATH courses numbered 210 or above.

The Minor in Statistics

Statistical analysis plays an important role in any evidence-based decision making. The statistics minor will provide students with a theoretical foundation of probability and statistics, an introduction to computing using statistical software, a foundation for applying statistical models to analyze data, and the skills to communicate their results. 

The statistics minor is useful for non-mathematical majors because it provides students with a deeper understanding of statistics and quantitative reasoning. In addition to having students work with data and research questions from a variety of disciplines, the minor will emphasize the importance of evidence-based, data-driven decisions and foster skills for students to be critical observers in society --- skills that complement and strengthen a range of majors and careers. 

The minor in statistics consists of five courses: MATH 171, MATH 232, MATH 231, MATH 338 and one upper-level course that either focuses on the theory of statistical inference (MATH 337; recommended for those applying to graduate school in statistics) or on the application of statistics in a specific discipline. The application of statistics in a specific discipline must be a 200- or 300-level discipline specific statistics course that does not have a MATH designation; Courses must be approved by the Mathematics Program Chair. Pre-approved courses include BIOL 220 Biostatistics and ECON 256 Applied Econometrics.

The Interdepartmental Major in Mathematics

The six mathematics courses that meet Set I requirements are MATH 170 (or its equivalent sequence MATH106 and MATH166), MATH 171, MATH 211, and three additional MATH courses chosen by the student with the approval of the advisor. Mathematics courses to be taken to satisfy Set II requirements will be determined by the student's prior preparation in mathematics and his or her educational objectives.

Computer Science:

Mission: The computer science program prepares individuals for entry into technical professions where they can contribute to production-level software solutions and continue to learn and adapt to new technologies.

Computer science is the study of how to automate problem solving with computers.  In the Internet age computers are used in nearly every facet of life, and programmers must understand the technical capabilities of computers and the technology requirements for problem domains. The computer science program at Moravian creates an environment for students to learn software development in teams for real-world clients, and provides students with opportunities for hands-on experience with technology.

Computer science offers a General track and a Data science track. CSCI 120, 121, 265, 244, 234 and 334 are required for either track.  The general track includes additional requirements within computer science as well as MATH 106/166 or MATH 170 as a co-requisite.  The data science track includes additional requirements within mathematics as well as courses in applications and ethics.

General Track:

General Track Required Courses

  • CSCI 120 Introduction to Computer Science
  • CSCI 121 Intermediate Software Development, prerequisite: C- or better in CSCI 120
  • CSCI 140 Discrete Structures for Computer Science or MATH 212 Discrete Mathematical Structures and Proof.  Students who complete MATH 212 cannot later earn credit for CSCI 140.
  • CSCI 265 Database Systems, prerequisite: C- or better in CSCI 120
  • CSCI 220.2 Introduction to DevOps, prerequisite: C- or better in CSCI 120
  • CSCI 244 Advanced Software Development, prerequisite: C- or better in CSCI 121
  • CSCI 234 Introduction to Software Engineering, prerequisite: C- or better in CSCI 244
  • CSCI 243.2 Preparing for a Computing Career, prerequisite: CSCI 120 and junior standing
  • CSCI 334 System Design and Implementation (WI), prerequisite: CSCI 234

General Track Electives

Students must complete three units of additional elective courses numbered 210-299 or 310-399, with at least two courses numbered 310-399. Students may count at most one unit of internship toward these three units. Students may count one of MATH 230 Mathematical Methods in Operations Research or MATH 258 Numerical Analysis as a 200-level elective in the major.

General Track Corequisites

  • MATH 170 Calculus 1 (or MATH 106 Analytic Geometry and Calculus I with Review, Part 1 and MATH 166 Analytic Geometry and Calculus II with Review, Part 2)

Data Science Track:

Data Science Track Required Courses

  • CSCI 120 Introduction to Computer Science
  • CSCI 121 Intermediate Software Development, prerequisite: C- or better in CSCI 120
  • CSCI 265 Database Systems, prerequisite: C- or better in CSCI 120
  • CSCI 244 Advanced Software Development, prerequisite: C- or better in CSCI 121
  • CSCI 234 Introduction to Software Engineering, prerequisite: C- or better in CSCI 244
  • CSCI 243.2 Preparing for a Computing Career, prerequisite: CSCI 120 and junior standing
  • CSCI 334 System Design and Implementation (WI), prerequisite: CSCI 234
  • Math 231 Mathematical Statistics 1
  • Math 337 Mathematical Statistics 2

Data Science Corequisites

  • MATH 170 Calculus 1 (or MATH 106 Analytic Geometry and Calculus I with Review, Part 1 and MATH 166 Analytic Geometry and Calculus I with Review, Part 2)
  • MATH 171 Calculus 2 (or MATH 106 Analytic Geometry and Calculus I with Review, Part 1 and MATH 166 Analytic Geometry and Calculus I with Review, Part 2)

One course in ethics:

  • NURS 360 Ethical Dilemmas in Healthcare
  • PHIL 222 Ethics
  • PHIL 224 Applied Ethics
  • PHIL 251 Philosophy of Technology
  • PHIL 257 Bio-Ethics and Social Justice
  • PHIL 259 Medical Ethics
  • PHIL 281 Topics in Ethics
  • PHIL 355 Meta-Ethics
  • Other ethics courses, to be approved by the student’s advisor, may apply

We recommend that students in this program complete the module on responsible conduct in research in CITI training (which is available free to faculty and staff), and report completion of that training to the advisor.  Students could contact the IRB Committee for access to this software.

One course in applications:

  • HLTP 230 Epidemiology
  • MGMT 311 Marketing Research (prereq:  MGMT 251; plus Math 107, Math 231 or ECON156)
  • BIOL 363 Genomics (prereqs:  BIOL 210 and permission of the instructor)
  • ECON 256 Applied Econometrics (prereqs: a course in statistics and ECON 152, which is recommended as the M4 for students in data science)
  • Honors, Independent Studies, and other applications courses may apply; consult with the advisor

One additional 300-level course in Mathematics or from the Applications list or one of the following courses from the Master of Science in Predictive Analytics (MS-PA)program:

  • MGMT 555, Business Research Methods
  • MGMT 556, Decision Analysis

With permission of the program director of the MSDA program, students may enroll in additional courses in the MSDA

Students who complete this program would have “Data Science” listed on their transcript, under “concentration.”  They are not eligible for the Informatics minor.  Students may, however, count Math 170 and 171, but not Math 231 and 337, towards the math minor, as these latter two courses are required within the major. 

Courses in Computer Science (CSCI) are listed below.

The Minor in Computer Science

The minor in computer science consists of CSCI 120, CSCI 121, and three other CSCI course units numbered above 110. One of the following courses may, with departmental consent, be counted toward the computer science minor: MATH 230, MATH 258, MATH 231; PHIL 211. With departmental consent, one course with significant computing content from another program may be counted as one of the three elective course units towards the computer science minor.

The Minor in Informatics

Informatics is the application of computing skills, statistical methods, and domain knowledge to obtain and analyze data in order to make decisions about organizations and society.

The minor in informatics consists of five courses: CSCI 120​; CSCI 265​; one course in statistical reasoning (MATH 107​, HLTP 189​, ECON 156​, or MATH 231​); one course in ethics (NURS 360​, IDIS 215, or a PHIL course with “Ethics” in the title​); and one course in applications (HLTP 230​, MGMT 311​, BIOL 363,​ ECON 256​). Other courses in statistical reasoning, ethics, or applications may be accepted with approval of the program director.

The Interdepartmental Major in Computer Science 

The six courses that compose Set I of the interdepartmental major in computer science include CSCI 120, CSCI 121, and four other CSCI courses numbered above 110, at least one of which is expected to be numbered 310-380 or 390-399. The additional courses in computer science and the six courses of Set II are selected by the student with the approval of the advisor.

Courses in Mathematics

MATH 100.2. Applications in Mathematics. Investigation of a variety of mathematical models. Models to be investigated will be chosen from the areas of game theory, network models, voting theory, apportionment methods, fair division, and probability and statistics. We will apply these models in such diverse fields as biology, sociology, political science, history, and psychology. Does not count towards the mathematics major or minor. One 100-minute period.

MATH 101.2. A History of Infinity. Human beings have always struggled with the concept of infinity. Philosophers and mathematicians have gone mad contemplating its nature and complexity—and yet it is a concept now routinely used by school children. We will trace the history of this mind-boggling concept from Archimedes to Cantor through the eyes of the mathematician. Does not count towards the mathematics major or minor. 

MATH 102.2. Mathematics and Origami. In this course, we will use origami (paper-folding) to explore topics in mathematics such as trisecting angles, solving cubic equations, and creating 3-dimensional polyhedra. In the process, we will see how mathematics has revolutionized origami over the past 50 years. Does not count towards the mathematics major or minor.

MATH 104. Quantitative Reasoning and Informed Citizenship. Quantitative reasoning skills to interpret and assess numerical arguments, with emphasis on issues relevant for informed and effective citizenship. Topics include creating and interpreting graphs and charts; single- and multiple-variable functions; linear, exponential, and logarithmic growth; indexes; inductive and deductive reasoning; decision theory; measures of center and spread of data; correlation; probability; expected value; experimental design; sampling and surveys. Three 70-minute periods. (F2) 

MATH 106. Analytic Geometry and Calculus I with Review, Part 1. Beginning calculus with extensive review of algebra and elementary functions. Topics include Cartesian plane, algebraic functions, limits and continuity, introduction to the concept of derivative as a limit of average rates of change, theorems on differentiation, and the differential. Continued in Mathematics 166. The course sequence of MATH 106 and MATH 166 is equivalent to MATH 170; credit may be earned for MATH 106 and MATH 166 or MATH 170, but not both. (F2) Prerequisite: Placement by the Mathematics and Computer Science Department. 

MATH 107. Elementary Statistics. Introduction to statistical concepts and methods without the use of calculus. Topics include descriptive statistics, elementary probability, discrete and continuous probability distributions, correlation and regression, estimation, and hypothesis testing. MATH 107 may not be taken for credit by students who have earned credit for ECON 156 or MATH 232. Three 70-minute periods. (F2) 

MATH 108. Functions and Derivatives with Applications. Emphasis on concepts and applications to business and social and natural sciences. Use of graphing calculators. Topics include linear functions, polynomial functions, exponential functions, average rate of change, instantaneous rate of change, the derivative, interpretations of the derivative, rules of differentiation, and applications of the derivative. Includes review of algebra and elementary functions. May not be taken for credit by students who have completed MATH 106 or MATH 170. (F2) Prerequisite: Placement by the Mathematics and Computer Science Department.

MATH 109. Mathematics for Design. Provides mathematical background and techniques useful to aspects of artistic design in the plane and in space. Essential mathematical concepts and tools applied to solve design problems. Topics include ratio and proportion, similarity, geometric constructions with Euclidean tools and dynamic geometry soft ware, properties of polygons and polyhedra, isometries and other geometric transformations in the plane and space, symmetry, and periodic designs, projections from space onto a plane. Spring. Three 70-minute periods. (F2) 

MATH 120. Math for Teaching I.  Mathematics for Teaching 1 is specifically designed for students pursuing a career in elementary and middle level education. The purpose of the course is to provide the mathematical background necessary for teaching elementary mathematics concepts, including: estimation, measurement, fractions and decimals, patterns and relationships, number systems, number relations, and number theory.  This course will emphasize the development of conceptual understanding, mathematical connections, critical thinking, and problem-solving strategies across mathematics content. (F2) 

MATH 121.2 Math for Teaching II.  Mathematics for Teaching 2 is specifically designed for students pursuing a career in elementary and middle level education. The purpose of this course is to provide the mathematical background necessary for teaching with confidence and imagination the basic concepts of mathematics as well as techniques of problem-solving. Topics included in this course: statistics, probability, geometry and measurement. Throughout, the emphasis will be on basic ideas, problem-solving, and the larger historical and cultural contexts of mathematics. Prerequisite: EDUC 100.2.

MATH 150.2. Introduction to Mathematical Research I. Wonder what is beyond Calculus?  Haven’t we solved everything already?   Curious about mathematical research?  This course will answer these questions by serving as an introduction to mathematical research. This group based seminar course will require students to develop a project, do a literature review, investigate a mathematical problem, and prepare a mathematical paper, poster, and presentation. NOTE:  This course is pass/no credit.  This course is also a repeatable course. Prerequisite: MATH 170 or  MATH 108 or MATH 166 with a grade of “C-” or better and no Senior standing.

MATH 166. Analytic Geometry and Calculus I with Review, Part 2. Topics include exponential and trigonometric functions and their derivatives, related rates, extremum problems, logarithmic curve sketching, antidifferentiation, the definite integral, the fundamental theorem of calculus, area under a curve, and applications to business and economics. The course sequence of MATH 106 and MATH 166 is equivalent to Mathematics 170; credit may be earned for MATH 106 and MATH 166 or  MATH 170, but not both. (F2) Prerequisite: MATH 106 with a grade of “C-” or better. 

MATH 170. Analytic Geometry and Calculus I. Review of real numbers, analytic geometry and algebraic and transcendental functions. Limits and continuity. Definition, interpretations, and applications of the derivative. Definite and indefinite integrals, including the fundamental theorem of calculus. May not be taken for credit by students who have earned credit for MATH 166. (F2) Prerequisite: Placement by the Mathematics and Computer Science Department. 

MATH 171. Analytic Geometry and Calculus II. Applications of the definite integral. Techniques of integration of both algebraic and transcendental functions. Indeterminate forms and improper integrals. Separate differential equations. Infinite sequences and series. (F2). Prerequisite: Placement by the Mathematics and Computer Science Department or completion of MATH 170 or  MATH 166 with a grade of “C-” or better. Note: Students who are placed by the department into MATH 171 and complete it with a grade of “B” or better will automatically receive credit for Math 170 if their transcript does not show credit for an equivalent course. 

MATH 211. Analytic Geometry and Calculus III. Vectors in the plan and three-space. Parametric equations and space curves. Polar, cylindrical and spherical coordinates. Calculus of functions of more than one variable, including limits, partial derivatives, directional derivatives, multiple integration, and applications. Prerequisite: Completion of Math 171 with a grade of “C-” or better. Note: Students who are placed by the department into MATH 211 and complete it with a grade of “B” or better will automatically receive credit for Math 171 if their transcript does not show credit for an equivalent course. 

MATH 212 (formerly 216). Discrete Mathematical Structures and Proof. Elementary mathematical logic and types of mathematical proof, including induction and combinatorial arguments. Set theory, relations, functions, cardinality of sets, algorithm analysis, basic number theory, recurrences, and graphs. Writing intensive. Prerequisite: MATH 171. Fall. 

MATH 220. Linear Algebra. Vector spaces and linear transformations, matrices, systems of linear equations and their solutions, determinants, eigenvectors and eigenvalues of a matrix. Applications of linear algebra in various fields. Prerequisite: MATH 171. Spring. 

MATH 230 (formerly 214). Mathematical Methods in Operations Research. Introduction to mathematical techniques to model and analyze decision problems. Linear programming, including sensitivity analysis and duality, network analysis, decision theory, game theory, queuing theory. Prerequisites: MATH 171. Spring, alternate years. 

MATH 231. Mathematics Statistics I. An introduction to the theory of probability and a calculus-based introduction to statistical probability models. Topics include, probability, discrete and continuous probability distributions, transformations of a single variable, and multivariate probability distributions. Prerequisite: MATH 171. Fall.

MATH 250.2. Introduction to Mathematical Research II. Wonder what is beyond Calculus?  Haven’t we solved everything already?   Curious about mathematical research?  This course will answer these questions by serving as an introduction to mathematical research. This group based seminar course will require students to develop a project, do a literature review, investigate a mathematical problem, and prepare a mathematical paper, poster, and presentation. NOTE:  This course is pass/no credit.  This course is also a repeatable course. Prerequisite: MATH 212 and no Senior standing.

MATH 251 . Actuarial Mathematics.  This course includes an introduction to interest theory; the time value of money.   Topics include introduction to interest, valuation of annuities, loan payments, bond valuation, depreciation, amortization schedules, and other topics related to the theory of interest.  This course is intended for those students interested in taking the Financial Mathematics (FM) Actuarial Exam. Prerequisite: MATH 171. Spring, alternate years. 

MATH 254 (formerly 221). Differential Equations. Various methods of solution of ordinary differential equations, including first-order techniques and higher-order techniques for linear equations. Additional topics include applications, existence theory, and the Laplace transform. Prerequisite: MATH 211. Spring. 

MATH 258 (formerly 225). Numerical Analysis. Numerical techniques for solving applied mathematical problems. Topics include interpolation and approximation of functions, solution of non-linear equations, solution of systems of linear equations, and numerical integration, with error analysis and stability. Prerequisites: MATH 171 and a course in computer science. Spring, alternate years. 

MATH 324 (formerly 327). Advanced Calculus. Differential and integral calculus of scalar and vector functions. Differential calculus includes differentials, general chain rule, inverse and implicit function theorems, and vector fields. Integral calculus includes multiple integrals, line integrals, surface integrals, and theorems of Green and Stokes. Prerequisite: MATH 211. Fall, alternate years. 

MATH 337 (formerly 332). Mathematical Statistics II. Development of statistical concepts and methods including point and interval estimation, sampling distributions, properties of estimators, and theory of statistical inference. Additional topics may be added as time allows such as: regression analysis, Bayesian inference, analysis of variance, chi-square tests, or nonparametric inference. Prerequisite: C- or better in MATH 231. Spring, alternate years. 

MATH 338 Applied Statistical Modeling.  Applied Statistical Modeling is offered as a second applied course in statistics in which students from any discipline will be able to experience how statisticians think and practice. Students will investigate different case studies and take a problem-based approach to learn how to determine and implement appropriate statistical modeling techniques. An emphasis will be placed on statistical writing and communication of results. Topics include: inference for one and two samples, multiple linear regression, one- and two-way ANOVA, chi-square tests and logistic regression. Other topics (such as factorial experiments, block, split-plot, and repeated measures designs, or an introduction to Bayesian modeling) may be substituted or added as time allows. Students will be conducting all data analyses using the statistical software, R. Prerequisite: C- or better in MATH 232. (Cannot take if completed the special topics course MATH 297 in Spring 2019.)

MATH 347 (formerly 313). Modern Algebra. Group theory, including structure and properties: subgroups, co-sets, quotient groups, morphisms. Permutation groups, symmetry groups, groups of numbers, functions, and matrices. Brief study of rings, subrings, and ideals, including polynomial rings, integral domains, Euclidean domains, unique factorization domains, and fields. Prerequisite: MATH 212 or permission of instructor. Fall. 

MATH 348 (formerly 340). WI:Higher Geometry. Topics in Euclidean two- and three-dimensional geometry from classical (synthetic), analytic, and transformation points of view. Transformations include isometries, similarities, and inversions. Construction and properties of two- and three-dimensional geometric figures. Brief study of some non-Euclidean geometries. Prerequisite: MATH 212 or MATH 220. Fall, alternate years. Writing-intensive. 

MATH 350.2. Introduction to Mathematical Research III. Wonder what is beyond Calculus?  Haven’t we solved everything already?   Curious about mathematical research?  This course will answer these questions by serving as an introduction to mathematical research. This group based seminar course will require students to develop a project, do a literature review, investigate a mathematical problem, and prepare a mathematical paper, poster, and presentation. NOTE:  This course is pass/no credit.  This course is also a repeatable course. Prerequisite: permission of instructor.

MATH 365 (formerly 329). Complex Analysis. Analytic functions, complex integration, application of Cauchy's theorem. Prerequisite: MATH 211. Spring, alternate years. 

MATH 366 (formerly 328). Introduction to Analysis. Rigorous study of real-valued functions, metric spaces, sequences, continuity, differentiation, and integration. Prerequisites: MATH 211 and MATH 212 or MATH 220. Spring, alternate years. 

MATH 370. Mathematics Seminar. A capstone course designed to review, unify, and extend concepts developed in previous mathematics courses. Students will read historical, cultural, and current mathematical material. They will express their mathematical understanding through writings, oral presentations, and class discussions. Assignments will include both expository and research-oriented styles of writing, including a significant individual research project. Prerequisite: MATH 212 and any 300-level course in mathematics. Fall.

MATH 190-199, 290-299, 390-399. Special Topics.
MATH 286, 381-384. Independent Study.
MATH 288, 386-388. Internship.
MATH 400-401. Honors.

Courses in Computer Science

CSCI 105. Fundamental Ideas in Computer Science. Emphasis on contributions that computer science has made to contemporary society. Topics include physical and logical aspects of computers, algorithms and problem-solving, introduction to programming, and simple computer architecture, supplemented by laboratory exercises in which students create programs or utilize existing programs. Recommended for those not intending a major or minor in the department. (F2)

CSCI 107.2. Introduction to 3D Printing and Design. This course provides an introduction to using 3D fused deposition modeling (FDM) printers. Additionally the course will cover the basics of creating models with a variety of software packages such as Tinkercad, Sculptris, OnShape, and OpenJSCAD, each of which presents a very different approach to creating models to be printed. No experience is necessary. All materials will be provided. Students will be expected to spend time outside of class in the 3D printing lab.

CSCI 120. Introduction to Computer Science. Introduction to the discipline of Computer Science with an emphasis on computer programming. Students will learn the process of writing programs to solve problems and visualize results from a variety of fields. Recommended for students intending to apply computer programming in their own area of concentration. Students will learn programming skills and discuss applications of these ideas. Weekly laboratories give students the opportunity for hands-on exploration of the material and the chance to solve real-world problems. (F4) 

CSCI 121. Intermediate Software Development. This course takes a deeper look into the process of writing correct and readable programs and further develops the mental model of memory. Using an object-oriented language, students learn how to utilize the principles of encapsulation, inheritance, and polymorphism to design and implement programs. Other topics include file input and output, exceptions, testing, and recursion.  Prerequisite: CSCI 120 (final grade of at least C– or better).

CSCI 140. Discrete Structures for Computer Science. Problem solving and programming require an understanding of logic, finite-space arithmetic, methods of organizing data, and algorithmic thinking. This course covers these topics and demonstrates their direct application in Computer Science. Completion of this course provides students with essential mathematical knowledge, skills, and abilities that are used throughout the Computer Science curriculum.  Students who complete MATH 212 cannot later earn credit for CSCI 140.

CSCI 217. Digital Electronics and Microprocessors. (Also Physics 217) Laboratory-oriented course in computer hardware for science, mathematics, and computer-science students. Topics include logic gates, Boolean algebra, combinational and sequential logic circuits, register-transfer logic, microprocessors, addressing modes, programming concepts, microcomputer system configuration, and interfacing. 

CSCI 220.2. Introduction to DevOps. A skills-based course that introduces students to techniques to automate processes in software development.  Topics include terminal basics, basic system administration (files, processes, users), virtualization, OS package management, library management, containerization, orchestration, and continuous integration/continuous deployment (CI/CD). Prerequisite: CSCI 120.

CSCI 222. Computer Organization. A study of what happens when a computer program is executed. We examine the organization of a modern computer from the perspective of a programmer; our examination focuses on the layers of abstraction between a high-level language program and its execution. Topics include the set of instructions that a processor supports, how a high-level language program is translated into this instruction set, how a processor carries out instructions, concurrency, the memory hierarchy, and storage systems. Prerequisite: CSCI 121.

CSCI 234. Introduction to Software Engineering. An introduction to professional software development using object-oriented techniques. Topics include the use of object-oriented design as a tool for building correct and maintainable software systems, test-driven development, best-practices in object-oriented design and development informed by component-based engineering, advanced object oriented language features, and languages for communicating design. Prerequisite: CSCI 244 (final grade of at least C– or better). 

CSCI 243.2. Preparing for a Computing Career. A course that considers the skills a student needs to prepare for the world of work. Topics include exploring areas of industry, resume/cover letter preparation, job/internship search preparation, interview skills, salary negotiation, and social media and professional etiquette in the workplace. Prerequisite: CSCI 120 and Junior/Senior Standing. 

CSCI 244. Data Structures and Analysis of Algorithms. This course challenges students to evaluate code in metrics other than correctness.  What is good code, and how do choices during design and implementation affect the quality of the code?  Topics include test-driven development (TDD), polymorphism as a problem solving technique, basic design patterns, measuring program efficiency, data structure selection, error handling with exceptions, and the use of third-party libraries.  Prerequisites: CSCI 121 (final grade of C– or better).

CSCI 260. Artificial Intelligence. Topics and methods for emulating natural intelligence using computer-based systems. Topics include learning, planning, natural-language processing, machine vision, neural networks, genetic algorithms. Prerequisite: CSCI 120. 

CSCI 265. Database Systems. Data file organization and processing, indexed data files and indexing techniques, database design; database applications; query languages; relational databases, algebra, and calculus; client-server models and applications; database system implementation and web programming. Prerequisite: CSCI 120 or permission of the instructor. 

CSCI 320. Networking and Distributed Computing. Theory and practice of concurrent programming. We examine the difference between shared- and distributed-memory models of computation, what problems are computable in parallel and distributed systems, the principle differences between concurrent and sequential programming, as well as data structures and algorithms for concurrent programming. Prerequisite: CSCI 244.

CSCI 330. Game Programming. Focus on the mathematics and algorithms necessary to create computer games and the software engineering principles used to manage the complexity of these programs. Topics include advanced programming in an object-oriented language, the mathematics of game programming, artificial intelligence, event-loop programming, and 2D graphics. Prerequisite: CSCI 244. 

CSCI 333. Operating Systems. The structure and organization of operating systems, how modern operating systems support multiprogramming (e.g., processes, threads, communication and synchronization, memory management, etc.), files systems, and security. Programming projects involve both using operating system services as well as the implementation of core operating system components. Prerequisites: CSCI 222 and CSCI 244.

CSCI 334. Systems Design and Implementation. Project-oriented study of ideas and techniques for design and implementation of computer-based systems. Topics include project organization, interface design, documentation, and verification. Prerequisites: CSCI 234 and senior standing. Writing-intensive. 

CSCI 335. Simulation. When real-world experiments are either too dangerous or too expensive to perform, computer simulation is used as an alternative. In addition to considering how to model real-world problems using computer simulation, this course studies other relevant topics including how to generate random data using a deterministic machine and how to collect and display data in a meaningful way.

CSCI 364. Foundations of Computing. Theoretical aspects of computing. Topics include formal languages (regular, context-free, and context-sensitive grammars), automata (finite-state machines, push-down automata, and Turing machines), limitations of respective computational models, and unsolvable problems. Prerequisite: CSCI 244. 

CSCI 190-199, 290-299, 390-399. Special Topics.
CSCI 286, 381-384. Independent Study.
CSCI 288, 386-388. Internship.
CSCI 400-401. Honors.