Courses

CS 617 ARTIFICIAL INTELLIGENCE   3.0 Credit(s)
Addresses foundational principles making computers learn, plan, and solve problems autonomously; and driving modern intelligent agents on real-world applications for contemporary problems, such as deep learning, and data flows.
Offered: All Semesters All Years

MK 676 DIGITAL ADVERTISING   3.0 Credit(s)
The course in digital advertising will cover a gap between traditional advertising and digital advertising, including mobile, Internet, viral media, paid and unpaid advertising. This course goes beyond using web metrics for advertising but instead focus on creating a unified advertising proposition that can be delivered in Omnichannel.
Offered: Late Spring Semester All Years

MK 677 CUSTOMER EXPERIENCE MANAGEMENT   3.0 Credit(s)
This course provides an understanding of customer experience management, as a collection of processes used to measure customers' interactions between customers and the organization throughout the customer lifecycle. Prerequisite: Take MK-661 MK-670 MK-674;
Offered: Fall Semester Even Academic Years

CS 648 INTRODUCTION TO SOFTWARE QA   3.0 Credit(s)
Introduction to Software Quality Assurance details key facets of software testing and testing theory. Students will utilize core testing theory to create test plans with meaningful test cases ensuring critical coverage of documented requirements. Prerequisite: Take CS-501

SW 676 SPEC INTEGRATED PRACTICE II:MSW CAPSTON   3.0 Credit(s)
This is the second of a two-semester specialized practice course.  In this culminating course, students will apply key content in the Master of Social Work curricula to design and defend a MSW Capstone project. The MSW Capstone project is a comprehensive demonstration of specialized practice integrated across all levels of social work practice in alignment with the mission of the School of Social Work.  Throughout this course students will demonstrate progress on their Capstone in accordance with defined benchmarks and a final product. Students will work collaboratively with their instructor, peers, and key stakeholders to reach the benchmarks, integrate learning, practice leadership skills, and demonstrate their ability to apply social work knowledge, values, skills and cognitive and affective processes. Pre-requisite= SW675 Prerequisite: TAKE SW-675
Offered: As Needed All Years

SW 680 SPECIALIZED PRACTICUM & SEMINAR II   3.0 Credit(s)
Second half of two-semester course where students participate in an approved, specialized, social work practice field placement with the focus on the development and application of skills and cognitive/affective process within specialized framework. Pre-requisite = SW678. Pre/co-requisite = SW676 Prerequisite: Take SW-678
Offered: As Needed Contact Department

CS 625 CRYPTOGRAPHY   3.0 Credit(s)
This course covers theoretical and practical aspects of modern applied computer cryptography. Topics include block and stream ciphers; hash functions, data authentication, and digital signatures. Special emphasis is given to public-key cryptosystems. The course includes use of various encryption methods in different programming systems. Prerequisite: Take CS-504 or CS-505
Offered: Fall, Spring & Late Spring Sem All Years

CS 624 HANDS - ON NETWORK SECURITY   3.0 Credit(s)
Designed for IT graduate students, this course uses VMWare of Connectix Virtual PC to simulate different environments. It examines networking security topics, firewalls (using Linux), packet filters, NAT, PAT, socks and HTTP proxies, public key infrastructure (using Microsoft Certification Server), encryption algorithms, decrypting passwords, dictionary decryption, brute force decryption, certificate servers, vulnerability assessment, identifying security holes, forensics, tracing, log analysis, Layer 5 vulnerabilities (Services/Daemons and OS), identifying denial of service attack (simulation), identifying a virus/work attack (simulation), and packet monitoring (sniffing). Prerequisite: Take CS-621 or CS-560
Offered: As Needed Contact Department

BUAN 660 APPLIED STATISTICS   3.0 Credit(s)
This course introduces students to basic mathematical and statistical methods and models, as well as their software applications for solving business problems and/or in making decisions. Included topics are linear regression, analysis of variance, introductory time series analysis & forecasting and several advanced applications of the general linear model. This course uses numerous case studies and examples from economics, finance, marketing, operations and other areas of business to illustrate the realistic use of statistical methods. Prerequisite: Take BUAN-651
Offered: All Semesters All Years

BUAN 670 DATA MINING   3.0 Credit(s)
Data mining involves decision making by detecting patterns, and cluster analysis. This course introduces data mining techniques, real-world applications and its challenges. A number of well-defined data mining tasks such as classification, estimation, prediction, affinity grouping and clustering, and data visualization will be discussed. The course will provide students with a sound understanding of how to utilize data mining to enhance business productivity in a variety of business applications. Prerequisite: Take BUAN-660
Offered: All Semesters All Years

BUAN 680 PRICING AND REVENUE ANALYTICS   3.0 Credit(s)
Pricing and revenue analytics is a set of practices and tools that firms use to optimize product & service choices, pricing, and promotion strategies. Students will be able to identify and develop opportunities for revenue optimization in different business contexts including the retail, telecommunications, entertainment, financial services, health care, manufacturing, among others. Adoption of these modeling techniques in the on-line advertising, online retailing, and online markets will also be discussed. Prerequisite: Take BUAN-651
Offered: All Semesters All Years

BUAN 655 DATABASE MANAGEMENT   3.0 Credit(s)
To compete in a data-driven world, data analytic skills and database skills are key. Before data is analyzed, correct data first needs to be chosen and pulled from a database within your organization or your client's organization. While the term big data is influenced by the rise of unstructured data (no-SQL database), structured data (SQL/relational database) remains a large and important component because structured data is driven by business processes and workflows. This course mainly focuses on process-driven/structured data and a relational database. This course is not designed to develop database building skills. A large focus of this course is placed on an understanding of database schema (or how business data is collected in relation to other business data) and SQL coding techniques for selecting the right data for the purpose of further analysis.
Offered: Fall Semester All Years

BUAN 690 APPLIED ANALYTICS PRACTICUM   3.0 Credit(s)
The course utilizes an integrative team project that gives students the opportunity to demonstrate an understanding of the core competencies taught throughout the program and apply them to real business concerns. Prerequisite: Take BUAN-651
Offered: All Semesters All Years

BUAN 651 INTRO TO DATA AND PROGRAMMING   3.0 Credit(s)
This course introduces fundamentals about data and the standards, technologies and methods for organizing, managing, curating, preserving, and using data. The course will teach students the use of software such as Python for data manipulation, analysis and visualization. The course also incorparates broader issues surrounding data, including technologies, behaviors, organizations, policies, and society. Special attention will be given to ethical issues surrounding data, soical and historical perspectives on data with ethics and policies to help students develop a workable understanding of current ethical issues in data science. Finally, the ethical issues will be addressed that arises throughout the lifecycle of data - from collection to storage to analysis and application.
Offered: Fall & Spring Semesters All Years

BUAN 665 DATA VISUALIZATION   3.0 Credit(s)
Visualizations are graphical depictions of data that can improve comprehension, communication, and decision making. This course is an introduction to the principles and techniques for data visualization. In this course, students will learn visual representation methods and techniques that increase the understanding of complex data and models. Emphasis is placed on the identification of patterns, trends and differences from data sets across categories, space, and time. Prerequisite: Take BUAN-651
Offered: All Semesters All Years