{"id":3310,"date":"2026-07-30T11:29:55","date_gmt":"2026-07-30T15:29:55","guid":{"rendered":"https:\/\/web.uri.edu\/mathematics\/?page_id=3310"},"modified":"2026-07-30T11:35:20","modified_gmt":"2026-07-30T15:35:20","slug":"ams","status":"publish","type":"page","link":"https:\/\/web.uri.edu\/mathematics\/academics\/course-descriptions\/ams\/","title":{"rendered":"AMS"},"content":{"rendered":"\n<h1 class=\"wp-block-heading\">Course Descriptions<\/h1>\n\n\n<section class=\"cl-wrapper cl-menu-wrapper\"><nav id=\"\" class=\"cl-menu  \" data-name=\"Course Descriptions\" data-show-title=\"0\"><ul id=\"menu-course-descriptions\" class=\"cl-menu-list cl-menu-list-no-js\"><li id=\"menu-item-3315\" class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-3315\"><a href=\"https:\/\/web.uri.edu\/mathematics\/academics\/course-descriptions\/\">Mathematics (MTH)<\/a><\/li>\n<li id=\"menu-item-3316\" class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-3316\"><a href=\"https:\/\/web.uri.edu\/mathematics\/academics\/course-descriptions\/ams\/\">Applied Mathematical Sciences (AMS)<\/a><\/li>\n<\/ul><\/nav><\/section>\n\n\n<h2 class=\"wp-block-heading\">Applied Mathematical Sciences (AMS)<\/h2>\n\n\n<div class=\"uri-kuali\">\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 393G<\/span>\n    <h3 class=\"uri-kuali-course-title\">Introduction to Predictive Analytics<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(3 crs.) Cross-listed as (AMS), DSP 393G. The course implements an active learning pedagogy for students to meticulously and systematically work with 'Big Data' to develop data-driven predictive models for decision-making. (Lec. 3) Pre: Pre: STA 308 or STA 409 or BAI 210; STA 305 or LTI\/DSP 110; and MTH 215. (B3) (D1) (GC)<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 450<\/span>\n    <h3 class=\"uri-kuali-course-title\">Introduction to the Mathematical Analysis of Data<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(3 crs.) Mathematical analysis of Data Science techniques and their implementation in python and R. Monte Carlo methods, Expectation-Maximization (EM) algorithms, Deep Learning, and Functional Analysis with spectral decomposition methods will be covered. (Lec. 3) Pre: MTH 215, MTH 451 and CSC 310 or permission of the instructor.<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 490<\/span>\n    <h3 class=\"uri-kuali-course-title\">Intermediate Topics in Applied Mathematics<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(1-4 crs.) Topics in applied and computational mathematics. Applications from engineering, biology, finance, data and network science, along with relevant numerical algorithms, will be considered. (Lec. 1-4) Pre: Permission of instructor. May be repeated for a maximum of 12 credits. Not for graduate credit.<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 528<\/span>\n    <h3 class=\"uri-kuali-course-title\">Applied Topology<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(3 crs.) Fundamental concepts of topology, metric spaces, homotopy equivalence. Simplicial complexes. Homology and cohomology groups. Exact sequences. Duality. Persistent homology, persistent diagrams, and their computation. Applications. (Lec. 3) Pre: MTH 215 and MTH 243 or permission of the instructor.<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 553<\/span>\n    <h3 class=\"uri-kuali-course-title\">Mathematical Methods for Data Science<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(3 crs.) Cross-listed as (AMS) DSP553. This course covers a wide range of mathematical tools from Discrete Mathematics, Calculus, Linear Algebra, and Probability Theory that arise in Data Science. Each mathematical construct is accompanied by examples of its use in solving practical problems in Data Science. (Accelerated Online Program) Pre: Enrollment in the Online Graduate Certificate in Data Science.<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 563<\/span>\n    <h3 class=\"uri-kuali-course-title\">Applied Mathematics in Data Science<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(3 crs.) Cross-listed (AMS), DSP 563. Introduction to mathematical foundations necessary to effectively study problems in data science and machine learning. Use linear algebra and optimization  pose and solve modern problems leveraging data from diverse applications. (Lec\/Accelerated Online Program) Pre: DSP 556.<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 590<\/span>\n    <h3 class=\"uri-kuali-course-title\">Advanced Topics in Applied Mathematics<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(1-4 crs.) Advanced topics of current interest in applied and computational mathematics. Applications from engineering, biology, finance, data and network science, along with relevant numerical algorithms, will be considered. (Lec.) Pre: Permission of instructor.<\/p>\n<\/div>\n\n<div class=\"uri-kuali-course\">\n  <div class=\"uri-kuali-course-header\">\n    <span class=\"uri-kuali-course-code\">AMS 699<\/span>\n    <h3 class=\"uri-kuali-course-title\">Doctoral Dissertation Research<\/h3>\n  <\/div>\n  <p class=\"uri-kuali-course-description\">(1-12 crs.) Number of credits is determined each semester in consultation with the major professor or program committee. (Independent Study) S\/U credit.<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Course Descriptions Applied Mathematical Sciences (AMS)<\/p>\n","protected":false},"author":581,"featured_media":0,"parent":54,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"class_list":["post-3310","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/pages\/3310","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/users\/581"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/comments?post=3310"}],"version-history":[{"count":3,"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/pages\/3310\/revisions"}],"predecessor-version":[{"id":3318,"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/pages\/3310\/revisions\/3318"}],"up":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/pages\/54"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/mathematics\/wp-json\/wp\/v2\/media?parent=3310"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}