{"product_id":"natural-language-process","title":"Natural Language Processing Solutions: An Intro to Evaluation \u0026 Implementation","description":"\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\" id=\"isPasted\"\u003e\u003cstrong style=\"box-sizing: border-box;\"\u003eCourse Description \u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003eThis course is an introduction to practical applications of Natural Language Processing, focusing on real world rather than algorithm development. This course is intended for learners with enough practical knowledge of their field of expertise with regard to their specific applications, and an awareness of the limitations of their specific domains\/technology.\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003eThis is an asynchronous, self-paced course with no live instructor. The flexible schedule allows learners to complete coursework and assignments at their own pace and time. \u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e \u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e\u003cstrong\u003eNote: Learners will be awarded a course completion certificate upon submitting the modules with an 80% completion score.\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e \u003c\/p\u003e\n\u003cfigure class=\"image image_resized\" style=\"width: 50.4%;\"\u003e\u003cimg\u003e\u003c\/figure\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e \u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e\u003cstrong style=\"box-sizing: border-box;\"\u003eLearning Outcomes\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003eAt the end of this course, you should be able to:\u003c\/p\u003e\n\u003cul\u003e\n\u003cli style=\"background-color: white; box-sizing: border-box; color: rgb(65, 65, 65);\"\u003eDescribe the capabilities of existing NLP systems.\u003c\/li\u003e\n\u003cli style=\"background-color: white; box-sizing: border-box; color: rgb(65, 65, 65);\"\u003eAnalyze the gap that exists between a stated scenario and the existing capabilities of NLP systems.\u003c\/li\u003e\n\u003cli style=\"background-color: white; box-sizing: border-box; color: rgb(65, 65, 65);\"\u003eTest solutions by measuring improvements introduced by NLP systems.\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003cp\u003e \u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e\u003cstrong style=\"box-sizing: border-box;\"\u003eCourse Schedule and Duration\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003eIt is recommended that you work through one module per week. The entire course is estimated to take 15.5 hours to complete. You should complete the modules in order. Complete one module per week.\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e \u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e\u003cstrong style=\"box-sizing: border-box;\"\u003eTarget Audience\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003eSales engineers\/business development executives, managers, college students, and anyone interested in learnign more about natural language processing.\u003c\/p\u003e\n\u003cp style=\"background-color: white; box-sizing: border-box; margin-top: 0px;\"\u003e \u003c\/p\u003e\n\u003cfigure class=\"table\" style=\"width: 520pt;\"\u003e\n\u003ctable style=\"border-collapse: collapse; box-sizing: border-box; empty-cells: show; max-width: 100%;\" border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"693\"\u003e\n\u003ctbody style=\"box-sizing: border-box;\"\u003e\n\u003ctr style=\"box-sizing: border-box; height: 14.1pt;\"\u003e\n\u003ctd style=\"border: 1pt solid windowtext; box-sizing: border-box; height: 14.1pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 140.45pt;\" width=\"187\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e\u003cstrong style=\"box-sizing: border-box;\"\u003eModule\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left-style: none; border-right: 1pt solid windowtext; border-top: 1pt solid windowtext; box-sizing: border-box; height: 14.1pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 379.55pt;\" width=\"506\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e\u003cstrong style=\"box-sizing: border-box;\"\u003eTopic \u0026amp; Readings\u003c\/strong\u003e\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"box-sizing: border-box; height: 17.95pt;\"\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left: 1pt solid windowtext; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 17.95pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 140.45pt;\" width=\"187\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e1\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left-style: none; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 17.95pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 379.55pt;\" width=\"506\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eHistory of Natural Language Processing\u003c\/p\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eWords vs. Concepts \u0026amp; Explicit vs. Implicit\u003c\/p\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eGeneral Domain \u0026amp; Specific Domain\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"box-sizing: border-box; height: 13pt;\"\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left: 1pt solid windowtext; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 13pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 140.45pt;\" width=\"187\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e2\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left-style: none; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 13pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 379.55pt;\" width=\"506\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eShallow NNs\u003c\/p\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eContextual Embeddings\u003c\/p\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eLM Capabilities\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"box-sizing: border-box; height: 17.05pt;\"\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left: 1pt solid windowtext; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 17.05pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 140.45pt;\" width=\"187\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e3\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left-style: none; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 17.05pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 379.55pt;\" width=\"506\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eTesting in General\u003c\/p\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eFactual correctness and Reasoning\u003c\/p\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eIntro to Prompt Learning \u0026amp; Engineering\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr style=\"box-sizing: border-box; height: 17.05pt;\"\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left: 1pt solid windowtext; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 17.05pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 140.45pt;\" width=\"187\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e4\u003c\/p\u003e\n\u003c\/td\u003e\n\u003ctd style=\"border-bottom: 1pt solid windowtext; border-image: initial; border-left-style: none; border-right: 1pt solid windowtext; border-top-style: none; box-sizing: border-box; height: 17.05pt; min-width: 5px; padding: 0in 5.4pt; user-select: text; vertical-align: top; width: 379.55pt;\" width=\"506\"\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003eCapstone Reflection Projection\u003c\/p\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\n\u003c\/table\u003e\n\u003c\/figure\u003e\n\u003cp style=\"box-sizing: border-box; margin-top: 0px;\"\u003e\u003cbr\u003e \u003c\/p\u003e","brand":"Purdue University","offers":[{"title":"Default Title","offer_id":43106835398723,"sku":"18263","price":129.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0567\/3402\/3747\/files\/800x800_Purdue_NaturalLanguageProcessing_v2.png?v=1776700953","url":"https:\/\/store-dev2.semi.org\/products\/natural-language-process","provider":"SEMI Dev 2","version":"1.0","type":"link"}