DATA-100 Spreadsheet Software (1 Credits)
Introduction to the use of spreadsheet software to manage and present data. Data entry, editing and formatting, relative and absolute addressing, formulas and built-in functions, sorting, database features, graphing, presentation quality output. Uses Microsoft Excel spreadsheet software.
DATA-100TR Transfer Elective (1-12 Credits)
DATA-101 Introduction to Data Analysis (4 Credits)
(Q) The course objective is to ensure that students gain knowledge and skills to gather, store, and manipulate data to conduct an analytical study including describing events that have already occurred, utilizing predictive and prescriptive analytical approaches, and exploiting the results. Topics include an overview of business analytics, decision support systems, business intelligence, data science, artificial intelligence, data mining, predictive analytics, prescriptive analytics, big data, and ethics. Spreadsheet and data analytics software are utilized.
DATA-200TR Transfer Elective (1-12 Credits)
DATA-299 Directed Study (1-2 Credits)
DATA-300TR Transfer Elective (1-12 Credits)
DATA-331 Introduction to Mgmt. Info. Systems (4 Credits)
The study of organizational use of information technologies, dealing with the planning, development, management and use of informational technology tools to help people perform tasks related to information processing and management. As a survey of MIS topics, this course does not teach technological proficiency; it teaches fundamental MIS concepts and effective communication of those concepts.
DATA-332 System Analysis & Design (4 Credits)
Introduction to information systems analysis and design using an object-oriented approach, and preparation for analyzing the information needs and processes of a business. Concepts and methodologies include Systems Development Life Cycle (SDL C), Object-Oriented Development Life Cycle (ODL C), properties of objects and classes, the Unified Modeling Language (UML) and visual modeling; systems analysis will be the main emphasis. Pre-requisite: DATA-331
DATA-340 Data Mining (4 Credits)
The course objective is to ensure that students gain knowledge and skills to recognize opportunities for data mining approaches and exploit the results. The course utilizes an applied approach to data mining concepts and methods including specific methods used for different domains of data such as text data, time-series data, sequence data, graph data, and spatial data. The course also covers applications such as stream mining, Web mining, ranking, recommendations, social networks, and privacy preservation. Prerequisites: CS 201, DATA 101, DATA-331 and one course from BUSN-211, MATH-130, MATH-330, PSYC-240 or SOAN-227. Minimum grade of C in DATA-101
DATA-360 Practicum in Data Science (4 Credits)
The course objective is to ensure that students gain knowledge and skills to manage and implement an analytics project. This project-based course will engage students in the complete life-cycle of a data analysis project, including: identifying data sources/acquiring data, importing and transforming data formats, data cleaning/wrangling, exploratory analysis, quantitative analysis, visualization, and communication of findings. A variety of data analytics software packages are utilized. NOTE: DATA 360 and 490 will meet jointly; however the DATA 360 project component will utilize a published case and the DATA 490 project component will utilize actual projects provided by firms. Prerequisites: DATA 101, CSC 201, and one of BUSN 211, MATH 330, PSYC240, SOAN 227. Minimum grade of C in DATA-101.
DATA-490 Senior Inquiry (4 Credits)
The course objective is to ensure that students gain knowledge and skills to manage and implement an analytics project. This project-based course will engage students in the complete life-cycle of a data analysis project, including: identifying data sources/acquiring data, importing and transforming data formats, data cleaning/wrangling, exploratory analysis, quantitative analysis, visualization, and communication of findings. A variety of data analytics software packages are utilized. NOTE: DATA 360 and 490 will meet jointly; however the DATA 360 project component will utilize a published case and the DATA 490 project component will utilize actual projects provided by firms. Prerequisites: DATA 101, CSC 201, and one of BUSN 211, MATH 330, PSYC240, SOAN 227. Minimum grade of C in DATA-101.
DATA-INTR Core Internship (0-12 Credits)