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MAT 3050 cov­ers Eu­clid­ean and hy­per­bolic geom­e­try in two and three di­men­sions from an ax­iomatic point of view. It ex­am­ines clas­si­cal the­o­rems as well as groups of trans­for­ma­tions.

MAT 3050 covers Euclidean and hyperbolic geometry in two and three dimensions from an axiomatic point of view. It examines classical theorems as well as groups of transformations.

This course ex­am­ines the his­tor­i­cal, philo­soph­i­cal, and so­ci­o­log­i­cal foun­da­tions un­der­ly­ing the de­vel­op­ment of Amer­i­can ed­u­ca­tional in­sti­tu­tions. The role of the schools, the aims of ed­u­ca­tion, di­verse learn­ers, the math­e­mat­ics cur­ricu­lum in New York State, legal prin­ci­ples that af­fect ed­u­ca­tion, and the role of state, local, and fed­eral agen­cies will be em­pha­sized.

This course examines the historical, philosophical, and sociological foundations underlying the development of American educational institutions. The role of the schools, the aims of education, diverse learners, the mathematics curriculum in New York State, legal principles that affect education, and the role of state, local, and federal agencies will be emphasized.

A pro­ject-based in­tro­duc­tion to com­pu­ta­tional think­ing and prob­lem solv­ing. Cov­ers a wide range of top­ics, in­clud­ing data vi­su­al­iza­tion, sta­tis­ti­cal tech­niques, sim­u­la­tions of dy­nam­i­cal sys­tems, com­pu­ta­tional tech­niques to un­der­stand data, using re­gres­sion to fit mod­els to data, as well as an in­tro­duc­tion to some more ad­vanced top­ics: Monte Carlo sim­u­la­tions, op­ti­miza­tion, dy­namic pro­gram­ming, image pro­cess­ing, nat­ural lan­guage pro­cess­ing, geospa­tial data analy­sis and cur­rent data sci­ence.

A project-based introduction to computational thinking and problem solving. Covers a wide range of topics, including data visualization, statistical techniques, simulations of dynamical systems, computational techniques to understand data, using regression to fit models to data, as well as an introduction to some more advanced topics: Monte Carlo simulations, optimization, dynamic programming, image processing, natural language processing, geospatial data analysis and current data science.

This course is de­signed to pre­pare stu­dents for an ad­vanced math­e­mat­ics cur­ricu­lum by pro­vid­ing a tran­si­tion from Cal­cu­lus to ab­stract math­e­mat­ics. The course fo­cuses on the processes of math­e­mat­i­cal rea­son­ing, ar­gu­ment, and dis­cov­ery. Top­ics in­clude propo­si­tional and first order logic, learn­ing proofs through puz­zles and games, ax­iomatic ap­proach to group the­ory, num­ber the­ory, and set the­ory, ab­stract prop­er­ties of re­la­tions and func­tions, el­e­men­tary graph the­ory, sets of dif­fer­ent car­di­nal­i­ties, and the con­struc­tion and prop­er­ties of real num­bers. Avatar and Header im­ages cre­ated with Hip­ster Logo Gen­er­a­tor http://​www.​hip​ster​logo​gene​rato​r.​com/

This course is designed to prepare students for an advanced mathematics curriculum by providing a transition from Calculus to abstract mathematics. The course focuses on the processes of mathematical reasoning, argument, and discovery. Topics include propositional and first order logic, learning proofs through puzzles and games, axiomatic approach to group theory, number theory, and set theory, abstract properties of relations and functions, elementary graph theory, sets of different cardinalities, and the construction and properties of real numbers. Avatar and Header images created with Hipster Logo Generator http://www.hipsterlogogenerator.com/

This course in­tro­duces the foun­da­tions of dis­crete math­e­mat­ics as they apply to com­puter sci­ence, fo­cus­ing on pro­vid­ing a solid the­o­ret­i­cal foun­da­tion for fur­ther work. Top­ics in­clude func­tions, re­la­tions, sets, sim­ple proof tech­niques, Boolean al­ge­bra, propo­si­tional logic, el­e­men­tary num­ber the­ory, writ­ing, an­a­lyz­ing and test­ing al­go­rithms.

This course introduces the foundations of discrete mathematics as they apply to computer science, focusing on providing a solid theoretical foundation for further work. Topics include functions, relations, sets, simple proof techniques, Boolean algebra, propositional logic, elementary number theory, writing, analyzing and testing algorithms.