Elizabeth Milonas’s Profile Faculty Toggle navigation

This openly avail­able model course con­tains course in­for­ma­tion, learn­ing out­comes, sug­gested weekly top­ics and sam­ple home­work as­sign­ments. This model course is paired with the model course hub which con­tains ad­di­tional re­sources for this course in­clud­ing ad­di­tional read­ing, in­struc­tional videos, course syl­labus, text­book in­for­ma­tion, col­lege re­source in­for­ma­tion, and SQL code for use in class and at home. The model course can be cloned and adapted by any fac­ulty mem­ber teach­ing this course.

This openly available model course contains course information, learning outcomes, suggested weekly topics and sample homework assignments. This model course is paired with the model course hub which contains additional resources for this course including additional reading, instructional videos, course syllabus, textbook information, college resource information, and SQL code for use in class and at home. The model course can be cloned and adapted by any faculty member teaching this course.

Fun­da­men­tal course in the basic con­cepts and prin­ci­ples of the Data Sci­ence do­main in­clud­ing: de­f­i­n­i­tion, frame­work, tech­niques, is­sues and busi­ness uses. Top­ics in­clude data col­lec­tion, pro­cess­ing and man­age­ment, ex­ploratory data analy­sis, data vi­su­al­iza­tion and pre­sen­ta­tion and eth­i­cal is­sues. Through case stud­ies as well as in­di­vid­ual and group pro­ject/as­sign­ments stu­dents use data sci­ence tech­niques and tools to solve busi­ness prob­lems and im­prove busi­ness de­ci­sion mak­ing.This site can be used as a start­ing place for cre­at­ing an OER.

Fundamental course in the basic concepts and principles of the Data Science domain including: definition, framework, techniques, issues and business uses. Topics include data collection, processing and management, exploratory data analysis, data visualization and presentation and ethical issues. Through case studies as well as individual and group project/assignments students use data science techniques and tools to solve business problems and improve business decision making.This site can be used as a starting place for creating an OER.

In this course, stu­dents de­velop a fun­da­men­tal and prac­ti­cal un­der­stand­ing of the Web based data­base do­main par­tic­u­larly NoSQL data­bases. Tra­di­tional re­la­tional data­base mod­els are re­viewed and NoSQL data­base mod­els such as key-value, doc­u­ment, colum­nar and graph are an­a­lyzed, em­ployed and prac­ticed. Query and re­trieval tech­niques used for Web data in con­nec­tion with NoSQL data­base mod­els are dis­cussed, com­pared and uti­lized. NoSQL data­bases such as Redis, Neo4j and Mon­goDB are ex­am­ined and uti­lized. In ad­di­tion, the im­pact of the ac­qui­si­tion and use of big data and NoSQL data­bases is dis­cussed in terms of eth­i­cal and moral im­pli­ca­tions.

In this course, students develop a fundamental and practical understanding of the Web based database domain particularly NoSQL databases. Traditional relational database models are reviewed and NoSQL database models such as key-value, document, columnar and graph are analyzed, employed and practiced. Query and retrieval techniques used for Web data in connection with NoSQL database models are discussed, compared and utilized. NoSQL databases such as Redis, Neo4j and MongoDB are examined and utilized. In addition, the impact of the acquisition and use of big data and NoSQL databases is discussed in terms of ethical and moral implications.