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Mathematics and Computer Science
Course Descriptions
Other courses:
Mathematics
Computer Science Courses

CSCI 107: Introduction to Web Programming
A broad introduction to World Wide Web programming and related technologies. Topics include Internet history and its architecture, managing an account on a Web server, HTML markup, use of style sheets (CSS), page layout design, introduction to interactive programming with JavaScript, the document object model (DOM), and HTML forms. This is a general audience course suitable for those with no prior programming experience. (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 109: Intro to Programming for Robots
This course introduces the basic elements of computer programming by using the Mindstorms programming environment. Students work in teams, writing programs to make their robots perform assigned tasks. The standard building blocks of programming (sequencing, repetition, selection) are developed in the userfriendly, iconbased, draganddrop Mindstorms environment. During the second half of the course, students program robots in Python and Java. Each student must have a laptop computer for each class session. This is a beginning course, designed for students with no programming experience. (Not open to students who have completed FIYS 113 or CSCI 112. Does not satisfy requirements for the CSCI major or minor.) (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 112: Computer Science I
Introduction to computer science. Topics include the basic building blocks of problem solving (sequence, selection, repetition), objectoriented programming, basic data structures and algorithms. A prior knowledge of computer science is not required, although a good background in high school Mathematics is recommended. Students may receive credit for this course based on the AP computer science exam. (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 212: Computer Science II
Continuation of Computer Science I. Emphasis on advanced data structures, algorithms, and objectoriented design. Topics include linked data structures, recursion, algorithm analysis, interfaces, and inheritance. Prerequisite: Computer Science 112 with a grade of C or better. (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 213: Intro to Computer Architecture
Computer architecture, including digital logic, modern CPU design, memory layout, assembly language programming, addressing techniques, input/output design, and interfacing with highlevel languages. Prerequisite: Computer Science 112. (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 214: Principles of Digital Logic
Basic logic, digital electronics, microcomputer architecture, and interfacing, with handson laboratory activity. Prerequisite: Computer Science 213. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 240: Intro to Computational Math
(Introduction to Computational Mathematics.) This course provides a survey of computational techniques and methods that are rooted in mathematics and computing. Topics covered include numerical differentiation and integration, numerical solutions to ordinary differential equations, nonlinear equations in one variable, and classification methods. Applications of the techniques to "reallife" problems encountered in economics, physics, and/or the life sciences is emphasized. Constructing computer programs to implement the techniques presented also is emphasized. Prerequisites: MATH 110 and CSCI 112.Crosslisted as: MATH 240 
CSCI 250: Programming for Data Applications
Introduction to dataoriented Python packages, decision trees, support vector machines (SVM), neural networks, and machine learning. Prerequisite: CSCI 112: Computer Science I. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 260: Symbolic Logic
An introduction to propositional and predicate logic. Topics include formal semantics, translation, natural deduction, quantification theory, and completeness. The relevance of logic to computer theory and artificial intelligence is stressed. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 270: Web Development
This course builds upon Web programming fundamentals. It includes a review of HTML and CSS fundamentals and detailed coverage of CSS topics including selectors, cascade, positioning, page layout techniques, CSS media queries, and responsive/mobile design techniques. The course provides an introduction to serverside scripting and server side includes, advanced CSS/JavaScript frameworks, responsive grid design, and user interface tools. Prerequisites: CSCI 107 and Art 142. Students completing the Digital Media Design minor must take Art 260 before taking this course. (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.)  jump to top

CSCI 312: ClientServer Web Applications
An indepth study of building Web applications using the clientserver model. Topics include an overview of HTML and HTML forms for collecting user data, clientserver interaction, CGI programming, storage and manipulation of server data using databases, and returning dynamic content to the client. Preprocessed HTML documents with PHP or Java Server Pages and Web session control with cookies and other useful objects. Additional topics may include the distributed object framework, XML for data extensibility, and an overview of Microsoft's Active Server Pages (ASP) and .NET platform for distributed Web applications. Prerequisite: Computer Science 212. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 317: Data Structures and Algorithms
The study of advanced data structures and algorithm analysis. Topics include trees, hash tables, heaps, sorting algorithms, and graph algorithms. The emphasis will be on applying data structures to design and implement efficient algorithms. Additional topics may include dynamic programming and computational complexity. Prerequisite: Computer Science 212.
(Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 318: Programming Languages
A study of different problem solving paradigms, and representative programming languages. Topics include imperative vs. functional vs. eventdriven vs. declarative paradigms, markup vs. computation, typing, memory organization, scope, and lifetime management. Lab exercises focus on working in the various paradigms, and the tradeoffs involved. Prerequisite: Computer Science 212. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 323: Cryptography
An introduction to cryptology and cryptanalysis, the making of codes and the breaking of codes. History and basic concepts. Classical ciphers and attacks on classical ciphers. Onetime Pad. Modern ciphers including DES, AES. Public key ciphers including RSA and DiffieHellman. Digital signatures. Additional topics may include Elliptic Curve systems, knapsack systems, and other cryptographic systems. Prerequisites: Mathematics 230 and Computer Science 212, or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: MATH 323 
CSCI 325: Artificial Intelligence
An introduction to AI via topics including tree and graph searches, minmax methods, alphabeta pruning, heuristics, backtracking, natural language processing, and computer vision. Prerequisite: Computer Science 212. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: NEUR 325 
CSCI 327: Introduction to Database Systems
An indepth study of proper methods of design for database systems, with an emphasis on the relational model. Topics include relational design, query languages, and transactional processing. Lab exercises focus on GUIdriven, SQLbased access as well as modern, multitier styles of design. Prerequisite: Computer Science 212. 
CSCI 334: Theory of Computation
This course covers fundamental ideas in the theory of computation, including formal languages, computability, complexity, and reducibility among computational problems. Topics include formal languages, finite state automata, Kleene's theorem, formal grammars, pushdown automata, contextfree languages, Turing machines, computability, Church's Thesis, decidability, unsolvability, and NP completeness. Prerequisites: CSCI 212 and Mathematics 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: MATH 334 
CSCI 336: Operating Systems
An introduction to modern operating systems and their most important features. Topics include multiprocessing, virtual memory, multithreading, concurrency, I/O, networking, security, and distributed computing. Students construct a major component of an operating system in C or C++. Prerequisites: Computer Science 212 and 213. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 350: Computer Vision & Machine Learning
This course introduces the fields of Computer Vision and Machine Learning. Computer Vision concepts covered include basic image processing techniques such as histogram normalization, color transformation, and filtering, and extraction techniques such as HOG, LBP, and SIFT. Machine Learning concepts such as clustering and deep neural networks are also introduced. Prerequisite: CSCI 212 (Experience with Python desirable). (Under the new GEC, this course meets the Quantitative Reasoning and Technology requirements. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 360: Mathematical Modeling
This course provides an introduction to the process and techniques of modeling physical problems, including computing strategies and analysis of results. The course emphasizes Python programming. It covers numerical methods including solutions to linear and nonlinear equations, solutions to ordinary and partial differential equations, finite elements, linear programming, and optimization algorithms. Prerequistes: MATH 210 and CSCI 112. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)  jump to top

CSCI 365: Algebraic Coding Theory

CSCI 375: Combinatorics & Graph Theory
Enumeration techniques with emphasis on permutations and combinations, generating functions, recurrence relations, inclusion and exclusion, and the pigeonhole principle. Graph theory with emphasis on trees, circuits, cut sets, planar graphs, chromatic numbers, and transportation networks. Additional topics from designs with emphasis on Latin squares, finite projective and affine geometries, block designs, and design of experiments. Prerequisite: Mathematics 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: MATH 375 
CSCI 417: Algorithms and Algorithm Analysis
The study of algorithms and their mathematical analysis. Divideandconquer, greedy, bruteforce, dynamic programming, backtracking, advanced tree and graph algorithms, bigO notation, case and amortized analysis. Prerequisites: Mathematics 230 and Computer Science 317. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 461: Compiler Design
An introduction to the design and construction of compilers for modern programming languages. Topics include grammars, formal language definition, abstract syntax trees, symbol tables, syntax and semantic checking, code generation, and optimization. Students construct a modern compiler for an objectoriented programming language. Prerequisites: Mathematics 230 and Computer Science 212 and 213. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 488: Senior Seminar in Computer Science
A seminarlike discussion of software engineering, objectoriented design, and largescale software development. Students will practice modern software engineering as well as read and present papers concerning the subject. Prerequisites: Computer Science 317, 318 and permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
CSCI 489: Advanced Topics in Computer Science
Special topics and projects in computer science, including but not limited to distributed systems, secure computing, Web development, userinterface design, and software engineering. Prerequisites: Computer Science 317, 318, and permission of instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)
Mathematics Courses

MATH 102: Fundamental Concepts of Mathematics
(Fundamental Concepts of Mathematics with Quantitative Problem Solving.) This course focuses on the development of the quantitative skills needed for quantitative courses of study at Lake Forest College. Students will work on problems requiring application of algebraic concepts such as polynomial operations, rational expressions and equations, linear and quadratic equations, functions and their graphs, and linear systems. This 0.50credit course meets twice weekly throughout the semester and is graded PassFail. . Instructor approval is required. No prerequisites. (Under the new GEC, this course meets the Quantitative Reasoning requirement.) 
MATH 103: Nature of Mathematics
Intended for students with primary interests in the humanities and social sciences. The course uses set theory, logic, and language as a foundation for studying a variety of topics central to the development of modern mathematics. Emphasizing the central role of language in mathematics, the course shows that mathematics is about communication of ideas. Topics will be explored through experimentation with computers where appropriate using games, puzzles, and group projects as well as lectures and discussions. Additional topics include codes and basic geometry. The course will focus on the interplay of different ideas. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 104: Elem Math from Advanced Standpoint
MATH 104: Elementary Math from an Advanced Standpoint
This course presents a critical examination of several topics from elementary mathematics. The course stresses three themes: mathematics in the liberal arts, mathematics from a historical perspective, and mathematics as a problemsolving activity. Topics to be covered include college algebra, numeration systems, nonbase10 representations, and elementary number theory including primes and factorizations, rationals as terminating and repeating decimals, irrationals, simple probability experiments, elementary set theory, and mathematical reasoning. Crosslisted as: EDUC 104 (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: EDUC 104 
MATH 105: Elementary Functions
Properties of functions with emphasis on polynomial, exponential, logarithmic, and trigonometric functions. Analytic geometry. (Not open to students who have completed Math 110 with a grade of C or better.) (Under the new GEC, this course meets the Quantitative Reasoning requirement.) 
MATH 108: Calculus Ia
(Calculus Ia: Introduction to Limits and the Derivative.) This course introduces the concept of the limit and the derivative. In so doing, related topics in trigonometry and college algebra also are reviewed, including pertinent aspects of functions, polynomials, rational expressions, and analytic geometry. This course is a required skillsbuilding course for students desiring to complete Math 109. (Credit cannot be earned in Math 108 after satisfactory completion of Math 110.) Prerequisite: By placement only. Not open to students who have completed Math 110 with a grade of C or better. This course is being offered on a pilot basis for the 20182019 and 20192020 academic years. (Under the new GEC, this course meets the Quantitative Reasoning requirement.) 
MATH 109: Calculus Ib
(Calculus Ib: The Derivative and its Applications.) This course is a continuation of Math 108 that further develops the concept of the derivative and its applications. Additional skillbuilding topics in trigonometry and college algebra, beyond those covered in Math 108, are covered as needed. The concept of the integral is also introduced. Satisfactory completion of both Math 108 and Math 109 is equivalent to the satisfactory completion of Math 110. (Credit cannot be earned in both Math 109 and Math 110.) Prerequisite: Completion of Math 108 with a grade of C or better, or permission of the instructor. This course is being offered on a pilot basis for the 20182019 and 20192020 academic years. (Under the new GEC, this course meets the Quantitative Reasoning requirement.) 
MATH 110: Calculus I
The calculus of functions of one variable. Limits, continuity, differentiation, and applications; a brief introduction to integration. Prerequisite: 3.5 years of high school mathematics (to include trigonometry) or Mathematics 105. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 111: Calculus II
The calculus of functions of one variable. Integration, applications of integration, sequences, and series. Prerequisite: Mathematics 110. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 115: Honors Calculus I
Theory and applications of the calculus of functions of one variable, including trigonometric and exponential functions. Limits, continuity, differentiation, integration, and applications. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 116: Honors Calculus II
Continuation of Mathematics 115. Integration and applications, sequences, infinite series. Prerequisite: permission of the instructor. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.)  jump to top

MATH 150: Intro Probability & Statistics
Designed for students in the social and life sciences. Discrete probability theory, distributions, sampling, correlation, and regression, Chi square and other tests of significance. Emphasis on the use of the computer as a tool and on applications to a variety of disciplines. Not open to students who have taken ECON/BUSN 180 or ECON/BUSN/FIN 130. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 160: Math Methods with Applications
(Mathematical Methods with Applications) Topics from applied mathematics, including equations, inequalities, functions and graphs, and basic properties of logarithmic and exponential functions. Introduction to limits, derivatives and antiderivatives. Applications to business, the social sciences, and the life sciences. (Not open to students who have completed Math 110 with a grade of C or better.) (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 161: Mathematical Modeling
Mathematical topics as needed to build and solve mathematical models of situations in the life, environmental, and economic sciences. Topics covered include discrete dynamical systems, difference equations, linear, quadratic, and exponential growth models, the logistic model, and examples of chaos in dynamical systems. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 210: Multivariable Calculus
Partial differentiation, the algebra and calculus of vectors, curves and their parameterization, multiple integration, Stokes's and Green's theorem, and applications. Prerequisite: Mathematics 111. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 211: Math of Chaos
A study of nonlinear dynamical systems, including iteration of functions, attracting and repelling periodic orbits, bifurcation, the period doubling route to chaos, complex dynamics, fractals, and Mandelbrot and Julia sets. Realworld implications and applications of chaos. Can meet the requirements for a 300levelorabove mathematics course on completion of an additional project approved by the instructor. Prerequisite: Mathematics 111. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 214: Differential Equations
Differential equation models, analytic solution techniques, qualitative solution concepts, and computer visualization for single equations and systems. Applications of differential equations. Prerequisite: Mathematics 210 or permission of the instructor. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 230: Abstract & Discrete Mathematics
Topics covered include logic and proofs, set theory, relations, cardinal numbers, countable and uncountable sets, permutations and combinations, graph theory, and group theory. Prerequisite: Mathematics 110. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 231: Linear Algebra
Vector spaces, linear independence, linear transformations, matrices, determinants, and applications to geometry. Prerequisite: Mathematics 230 or permission of the instructor. (Under the new GEC, this course meets the Quantitative Reasoning requirement. Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 240: Intro to Computational Math
(Introduction to Computational Mathematics.) This course provides a survey of computational techniques and methods that are rooted in mathematics and computing. Topics covered include numerical differentiation and integration, numerical solutions to ordinary differential equations, nonlinear equations in one variable, and classification methods. Applications of the techniques to "reallife" problems encountered in economics, physics, and/or the life sciences is emphasized. Constructing computer programs to implement the techniques presented also is emphasized. Prerequisites: MATH 110 and CSCI 112. (Under the new GEC, this course meets the Technology requirement.)Crosslisted as: CSCI 240 
MATH 250: Intro to Statisical Programming
(Introduction to Statisical Programming.) Introduction to data analysis programming using R. Topics include: data cleaning, data visualization, hypothesis testing, simple and multiple regression, time series analysis, analysis of variance, nonparametrics, and categorical data analysis. No previous programming experience required. Prerequisite: Math 150: Introduction to Probability & Statistics, E/B/F 130: Applied Statistics, PSYC 222: Research Methods & Statistics II, or permission of the instructor.  jump to top

MATH 310: Complex Analysis
Study of functions of one complex variable. Analytic functions, complex integration, Cauchy's theorem, complex power series, and special functions. Applications to other areas of mathematics and to mathematical physics. Prerequisites: Mathematics 210 and 230 or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 311: Introduction Real Analysis
A rigorous course covering the following introductory real analysis topics: axioms for the real numbers, sequences, boundedness, limits, monotone functions, continuity, uniform continuity, Cauchy criterion for convergence, cluster points, compactness, differentiability, integration, and infinite series. Prerequisites: Mathematics 210 and 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 320: Mathematical Methods
Applied mathematics for scientists. Topics typically include series approximations to functions, matrices and eigenvectors, vector analysis, special functions, ordinary and partial differential equations, orthogonal polynomials, asymptotic techniques, boundary value problems, and numerical methods. Four hours of lecture per week. Prerequisites: Physics 121 (or 111) and Mathematics 210. May be taken as a tutorial. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: PHYS 320 
MATH 323: Cryptography
An introduction to cryptology and cryptanalysis, the making of codes and the breaking of codes. History and basic concepts. Classical ciphers and attacks on classical ciphers. Onetime Pad. Modern ciphers including DES, AES. Public key ciphers including RSA and DiffieHellman. Digital signatures. Additional topics may include Elliptic Curve systems, knapsack systems, and other cryptographic systems. Prerequisites: Mathematics 230 and Computer Science 212, or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: CSCI 323 
MATH 329: Number Theory
Mathematical induction, divisibility properties of integers, prime numbers, and congruences. Prerequisite: Mathematics 230 or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 330: Modern Algebra I
A study of algebraic structures with emphasis on groups, rings, and fields. Prerequisite: Mathematics 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 331: Modern Algebra II
Additional topics in modern or linear algebra such as field extensions, Galois Theory, group conjugacy, modules, eigenvalue theory, dual spaces, and unitary spaces. Prerequisite: Mathematics 330 or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 334: Theory of Computation
This course covers fundamental ideas in the theory of computation, including formal languages, computability, complexity, and reducibility among computational problems. Topics include formal languages, finite state automata, Kleene's theorem, formal grammars, pushdown automata, contextfree languages, Turing machines, computability, Church's Thesis, decidability, unsolvability, and NP completeness. Prerequisites: CSCI 212 and Mathematics 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: CSCI 334 
MATH 340: Geometry
Selected topics from affine, Euclidean, nonEuclidean, projective, and differential geometry. Prerequisite: Mathematics 230 or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 350: Mathematical Probability
Discrete and continuous probability. Distributions, the law of large numbers, the central limit theorem, random variables, and generating functions. Prerequisites: Mathematics 210 and 230 or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)  jump to top

MATH 360: Mathematical Modeling
This course provides an introduction to the process and techniques of modeling physical problems, including computing strategies and analysis of results. The course emphasizes Python programming. It covers numerical methods including solutions to linear and nonlinear equations, solutions to ordinary and partial differential equations, finite elements, linear programming, and optimization algorithms. Prerequistes: MATH 210 and CSCI 112. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 365: Algebraic Coding
A study of the algebraic structure of codes designed to transmit messages through a noisy channel in an efficient and relatively errorfree fashion. Topics include finitedimensional vector spaces over a finite field and the connection between coding theory and areas such as geometry, combinatorics, and number theory. Prerequisite: Mathematics 231 or permission of the instructor. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 375: Combinatorics & Graph Theory
Enumeration techniques with emphasis on permutations and combinations, generating functions, recurrence relations, inclusion and exclusion, and the pigeonhole principle. Graph theory with emphasis on trees, circuits, cut sets, planar graphs, chromatic numbers, and transportation networks. Additional topics from designs with emphasis on Latin squares, finite projective and affine geometries, block designs, and design of experiments. Prerequisite: Mathematics 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.)Crosslisted as: CSCI 375 
MATH 410: Topology
Point set topology. Such topics as topological spaces, separation axioms, covering properties, metrization, convergence and completeness, and homotopy theory. Prerequisite: Mathematics 230. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 411: Topics in Modern Analysis
Introductory notions of functional analysis. Banach spaces, integration and measure, Hilbert spaces, and commutative Banach algebras. Prerequisite: Mathematics 311. (Under the old GEC, this course meets the Natural Science & Mathematics requirement.) 
MATH 450: Mathematical Statistics
A mathematical study of such topics as estimation of parameters, confidence intervals and tests of hypotheses, decision theory, regression, analysis of variance, and nonparametric methods. Prerequisite: Mathematics 350. (Under the new GEC, this course meets the Senior Studies requirement.) 
MATH 499: Great Theorems of Mathematics
Seminar course to introduce students to various masterpieces in the development of mathematics. Some of the most historically important proofs and ingenious logical arguments from mathematics will be presented and discussed. An emphasis will be placed on the interconnectedness among various subject areas within mathematics. Prerequisite: permission of the instructor.