This Sample Program Pathway is designed to provide an example of course selections in a term by term sequence. Please see an Academic Advisor for a plan specific to your academic needs.
Description: In this course, students will learn how to identify data sources and evaluate whether data is credible and relevant. The course will introduce techniques to cleanse, analyze, and manage data. Visualization tools are covered in the course to assist in identifying and communicating data patterns and trends. Presentation of data findings and communicating meaning through storytelling is an important element of this course. In addition, students will gain an understanding on the impact of data in our society. This course is data literacy for all.
Description: This course will introduce students to the field of data preparation and visualization including design and hands-on experience with Tableau. Students will learn how to collect, transform, curate, and analyze datasets. The course will introduce students to design and build principles for telling stories for effective communications to facilitate data-driven decision-making, provide insights, and help speed up organizations that are data rich and information poor.
Notes: Fall Only
Prerequisites: MAT 0200 or MAT 1120
Description: Introduction to database management systems. Discussion of database environments, design, planning, implementation and administration in a relational model environment. Students will design and develop a simple database and implement a portion of this application including forms, queries and reports. Emphasis on database design techniques, normalization and the SQL database language.
Prerequisites: MAT 0200 or MAT 1120
Description: Use word processing, spreadsheet, database and presentation software applications to create reports, spreadsheets, databases and presentations for business and other applications.
Term hours subtotal:
12
Description: An introductory course in data science for students interested in information technology, computer science, and related fields. Topics include curation of data; enhanced data visualization; statistical models, estimation, and prediction; and applications of data science.
Notes: Spring Only
Prerequisites: MAT 0300 and Other (with a grade of "C" or better)
Description: Introduction to database management system in a client/server environment. The course covers Structured Query Language (SQL) and development and administrative tools. Students are taught to create and maintain database objects and to store, retrieve and manipulate data, and create blocks of application code that can be shared by multiple forms, reports, and data management applications.
Notes: CIS-2165 is a prerequisite Not offered Summer term.
Prerequisites: CIS 2165
Description: This course introduces students to analyzing data using Python. The basics of Python will be taught. Students will learn how to obtain, cleanse and prepare data for analysis. Data analytic and statistical tools will be used to visualize data, predict outcomes and categorize data.
Prerequisites: MAT 0200
Description: Students will learn techniques to properly manage large and multi-sheet spreadsheets, use spreadsheets to arrange and manage data, develop advanced spreadsheet formulas and functions, perform "What-If" analysis using spreadsheet tools and design and create end-user spreadsheet applications.
Prerequisites: BIS 1120 or BIS 1221
Term hours subtotal:
14
Description: Introduction to computer networking. Topics include network standards and the Open Source Interconnection (OSI) model, topologies and Ethernet standards, network hardware, remote connectivity, wireless networking, in-depth TCP/IP, network security, network troubleshooting and network management.
Description: Students will learn how to obtain, cleanse, and prepare data, use supervised models to predict and categorize data, and present their findings.
Notes: CIS-2266 is a prerequisite
Prerequisites: CIS 2266
Term hours subtotal:
6