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UW TACOMA
BUSINESS ADMINISTRATION (TACOMA CAMPUS)
BUSINESS ANALYTICS (UW TACOMA)

Detailed course offerings (Time Schedule) are available for

TBANLT 411 Data Management (5)
Focuses on the skills and knowledge necessary to acquire, model, store, transform, manage and represent data, and how to convert that data to information for desired outcomes in context of small and big data. Course overlaps with: T INST 311 and CSS 475. Recommended: proficiency in Excel/spreadsheets.

TBANLT 433 Programming for Data Analytics (5)
Provides an introduction to R programming and Python for addressing business analytics problems. Fundamentals of R and Python, data structures and their operators are covered. Use of packages and libraries for analytics, visualization, and data structure manipulation is emphasized. Business and predictive analytics topics will be introduced with programming solutions. Recommended: proficiency in Excel/spreadsheets.

TBANLT 450 Decision Modeling (5)
Introduces the development, implementation, and utilization of business models for managerial decision making. It covers formulation of models and interpretation of the information a model produces. Some of the deterministic optimization techniques (e.g. linear/nonlinear models) and probabilistic decision-making techniques (e.g. network models and decision trees) are covered. Course overlaps with: QMETH 450. Prerequisite: either TMATH 110, T BGEN 200, QMETH 201, STAT 220, STAT 221/CS&SS 221/SOC 221, or STAT 311.

TBANLT 460 Predictive Analytics (5)
Covers popular methods in predictive analytics including association rules, classification, regression trees, logistic regression and introduces cutting edge interactive data-visualization tools and data reduction techniques. Prerequisite: either TMATH 110, TMATH 390, T BGEN 200, QMETH 201, STAT 220, STAT 221/CS&SS 221/SOC 221, STAT 311, or T BUS 301.

TBANLT 480 Social Media Management and Analytics (5)
Focuses on the primary concepts, methods, tools and solutions to develop a social media strategy, and to collect, process and transform social media data into information processes, knowledge, actionable decisions and processes. Covers how organizations make use of social media as a strategy to gain a competitive advantage. Course overlaps with: MKTG 466. Recommended: proficiency in Excel/spreadsheets.

TBANLT 485 Business Intelligence (5)
Focuses on foundations of data and analytics. Explains concepts by examining innovative uses of information systems, data, and analytics to support managerial decision-making. Explores how to collect, store, manage, and convert data into information, knowledge, and actionable insights. Course overlaps with: I S 451. Recommended: proficiency in Excel/spreadsheets; and either TBANLT 411, or familiarity with data and database management concepts.

TBANLT 490 Special Topics in Business Data Analytics (1-5, max. 5)
Study and research on topics of current concern to faculty and students in the area of business data analytics. Only offered when allowed by faculty availability and sufficient student interest. Seminar content to be announced in advance of scheduled offerings.

TBANLT 510 Business Analytics (4)
Focuses on foundations of data and analytics-driven decision making. Explains the concepts with innovative uses of information systems, data, information, knowledge and analytics to support managerial decision-making. Explores how to collect, store, manage and convert data to information, knowledge and actionable insights.

TBANLT 520 Analytics Strategy and Big Data Management (4)
Focuses on how organizations need to make analytics part of their organizational strategy, and how they can implement analytics projects successfully by following sound project management principles. It focuses on strategy definition, initiating, planning, executing, controlling and completing analytics projects in a variety of environments for sustainable competitive advantage.

TBANLT 530 Business Process and Workflow Analysis (4)
Focuses on how organizations can evaluate, design and implement sound business process management practices, and integrate analytics into their business processes and workflows for maximum performance.

TBANLT 540 Applied Regression Models (4)
Focuses on statistical foundations of decision making processes. Topics may include multiple linear regression, models for quantitative and qualitative predictors, building regression models, autocorrelation, non-linear regression, piecewise linear regression, inverse prediction, weighted least squares, ridge regression, robust regression and non-parametric regression.

TBANLT 541 Advanced Modeling for Data Analytics (4)
Introduces a theoretical and practical understanding of advanced data analytics techniques including but not limited to: applications of support vector machines, applications of supervised and unsupervised learning methods, and applications of Bayesian and ensemble methods. Provides hands-on experiences in applying these techniques to real-world business problems. Offered: Sp.

TBANLT 550 Analytical Decision Making (4)
Focuses on the skills and knowledge necessary for mastery of the use of quantitative modeling tools and techniques to support decision analysis. Some of the deterministic optimization techniques (e.g. linear, nonlinear, integer optimization, network models) and uncertain decision making techniques (e.g. decision trees, transportation models, queuing theory) are covered.

TBANLT 560 Data Mining (4)
Focuses on some of the primary data mining topics (descriptive, predictive and prescriptive) through advance analysis of datasets. Students will become acquainted with both the strengths and limitations of various data mining techniques like Classification, Association analysis and Cluster analysis. Course overlaps with: MSIS 510 and MSIS 522.

TBANLT 570 Text Mining (4)
Focuses on some of the primary mining techniques for analyzing text data. These will be used to discover interesting patterns, extract useful knowledge, and support decision making. Topics like natural language processing, document representation, text categorization, text clustering and topic modeling will be covered. Course overlaps with: MSIS 541.

TBANLT 580 Social Media Analytics (4)
Focuses on some of the primary concepts, methods, tools and solutions to develop a social media strategy, and to collect, process and transform social media data into information processes, knowledge, actionable decisions and processes. It also covers how organizations make use of social media as a strategy to gain a competitive advantage.

TBANLT 585 Cognitive Analytics (4)
Focuses on foundations of cognitive analytics. Evaluate the concepts with innovative uses of cognitive solutions to either solve existing business problems or create new business opportunities, and improve the performance of organizations. Analyze how to utilize cognitive tools, assistants, collaborators and coaches effectively.

TBANLT 590 Special Topics in Business Analytics (2-4, max. 4)
Advanced course offerings designed to respond to faculty and student interests and needs. Topic will vary. Only offered when allowed by faculty availability and sufficient student interest. Content to be announced in advance of scheduled offerings.

TBANLT 591 Applied Project: Digital Transformation Lab I (2)
Focuses on how to apply the concepts, methods and solutions associated with data, analytics, smart machines and digital solutions to real opportunities in an application domain. Topics will include, but are not limited to: analysis of organization and market demand, business model development, opportunity analysis for digital transformation.

TBANLT 592 Applied Project: Digital Transformation Lab II (2)
Focuses on processes performed to analyze and plan digital transformation and innovation to a wide variety of opportunities and challenges. Topics will include, but are not limited to: requirements gartering, defining scope, risk analysis, detailed transformation and technology planning.

TBANLT 593 Applied Project: Digital Transformation Lab III (2)
Focuses on processes performed to design and develop data and digital solutions to a wide variety of opportunities and challenges. Topics will include, but are not limited to: collection, storage, analysis of data and development of digital solutions.

TBANLT 594 Applied Project: Digital Transformation Lab IV (2)
Focuses on processes performed to prototype data and digital solutions to a wide variety of opportunities and challenges. Topics will include, but are not limited to: develop, prototype and lessons learned, analyze findings, recognize ethical dilemmas and social responsibilities.

TBANLT 600 Independent Study or Research (2-4, max. 4)
Provides an opportunity to work independently exploring specific data and business analytics topics in greater depth. The student must develop a research proposal and make arrangements with a faculty member to supervise the project prior to course registration. permission of faculty is required.

TBANLT 601 Internship (2-4, max. 4)
Provides students with practical knowledge and experience in a private or public work environment. Gives students opportunities to develop a strategic plan under faculty guidance, and to perform field work utilizing the skills developed in the classroom. Permission of faculty is required.