Note: Enrollment in MSBA courses is limited to students enrolled in the MSBA program.
BAX 401: Introduction to Business Analytics
Through case studies, students are introduced to the process of analyzing raw data to gain profitable business insight. Applications selected across organizational functions include prediction, process improvement, and general operational decision-making.
BAX 402: Organizational Issues in Implementing Analytics
Students learn about the evolution of analytics in business, assembling and managing analytics teams, and most broadly, the decision life-cycle. In particular, they focus on structuring communications to improve buy-in from peers and non-quantitatively-inclined colleagues.
BAX 403: Organizational Effectiveness Workshop
Workshop participants work on leadership, communication and project management skills as they learn about the business, legal and societal contexts in which analytics is applied. Particular emphasis is placed on privacy, data security, responsibility, and ethics.
BAX 411: Problem Structuring
Students structure business issues using analytic frameworks (such as utility theory, decision trees, and influence diagrams) and techniques (such as simulation and optimization) for modeling business problems. Topics include uncertainty modeling, multi-criterion optimization, and consensus building.
BAX 421: Data Management
Students focus on the extraction, assembly, storage and organization of data. Specific topics include extract-transform-load (ETL), multi-dimensional databases and online analytical processing (OLAP), data warehousing, SQL, and non-relational data (such as NoSQL, multi-media, streaming, networks, and text search).
BAX 422: Big Data
This highly interactive, solution-focused course introduces students to applications involving standard, streaming, and network data. Students gain facility with highly scalable technologies used to process and analyze big data for a variety of management challenges.
BAX 423: Data Design and Representation
Students learn computational reasoning about data representations. Topics include mapping conceptual data models to relational structures, database architectures, and design tradeoffs.
BAX 431: Data Visualization
Students learn to extract insights using visualization tools in R, Python, ManyEyes, HTML/CSS, and D3.js. Topics include standard formats (such as histograms, boxplots, and dashboards), and specialized visualization formats (such as 3D, animation, word clouds, tree mapping, dendograms, and audio streaming).
BAX 441: Statistical Exploration and Reasoning
Students learn to use statistical reasoning and techniques to draw appropriate inferences from data. Students learn to obtain preliminary insights and form initial hypotheses through exploratory data analysis (EDA).
BAX 442: Advanced Statistics
Participants continue to explore statistical reasoning using advanced methods such as maximum likelihood estimation (MLE), Bayesian models, nonparametric models, Monte Carlo Markov Chain (MCMC), time series analysis, model specification, model selection, and dimension reduction.
BAX 443: Analytic Decision Making
Using spreadsheets and specialized modeling tools, students continue to explore structured problem solution through techniques such as meta-heuristics, Monte Carlo simulation, and mathematical optimization.
BAX 452: Machine Learning
This class will address construction of algorithms for learning from data, and the process for deriving business intelligence. Topics include supervised and unsupervised learning, reinforced learning, automated neural networks (ANN), scalable and parallel algorithms, clustering and dimension reduction.
BAX 453: Application Domains
Participants explore contemporary and emerging domains for high-yield applications of analytics. Examples include social network analytics, search analytics, health care analytics, internet of things (IOT), supply chain and operations analytics, and marketing analytics.
BAX 461: Practicum Initiation
In their first practicum course, students form teams, scope their project in light of team capability and business opportunity, create a preliminary structure and solution approach for the core problem, and assess data quality and project risks.
BAX 462: Practicum Elaboration
Building on the first course, teams continue to refine their chosen problem and draw insights from exploratory data analysis. They execute data extract/transform/load (ETL) operations, design data storage structures for future analysis, begin to experiment with appropriate solution methods, and design dashboard mock-ups for outputs.
BAX 463: Practicum Analysis
The focus is on implementing the selected analytic approach. This iterative process requires revisiting and refining assumptions and analysis, translating model results into client’s decision and operational requirements, and linking analytics to dashboards and functional prototypes.
BAX 464: Practicum Implementation
In the final phase, project teams complete their analysis, lay out a client deployment plan, and obtain client buy-in. This course culminates in a project presentation, preferably including representatives from the client organization.