From data mining to econometrics, our curriculum embraces the latest approaches and developments in the data analytics field. We also offer a number of cutting-edge elective classes that allow students to explore concepts in more detail or develop category-specific skills and knowledge.
CORE COURSES
Take all of the following:
| Course Number & Description | Course Title | Units |
|---|---|---|
| GSB 503 Collaborative business project with a client organization that allows graduate level students the opportunity to apply knowledge, skills and competencies to address a business problem. Small teams work in collaboration with a client organization and a faculty advisor. A formal written proposal must be accepted by the Associate Dean of OCOB Graduate Programs before work begins. The project may last up to one year. | Collaborative Industry Project | 4 |
| GSB 518 Statistics background needed for analysis of business data and econometrics. Topics include basics of probability theory, random variables, distribution functions, conditional distributions, independence, expectations, covariance, correlation, random samples, estimation, asymptotic theory, hypothesis testing, and confidence intervals. | Essential Statistics for Business Analytics | 4 |
| GSB 520 Exploration of data management including relational databases, data warehouses, and NOSQL databases. Foundation for analyzing, designing, implementing and using information repositories in a business environment. Topics include the database development life cycle, data modeling, SQL programming, data quality and integration. | Data Management for Business Analytics | 4 |
| GSB 530 Exploration of the concepts, tools and techniques of data mining in the business context, using case study and problem-solving approaches. Topics include multidimensional data modeling, predictive analytics, pattern discovery, forecasting, text mining, and data visualization. | Data Analytics and Mining for Business | 4 |
| GSB 544 Use of computers for advanced data analysis in business analytics. Topics include computer programming using statistical software, data gathering and cleaning, and machine learning. | Computing and Machine Learning for Business Analytics | 4 |
| GSE 519 Identification and estimation of linear and nonlinear regression models for analyzing business data. Topics include multiple linear regression; model selection; robust standard errors; instrumental variables; maximum likelihood estimation; logit/probit, ordered logit/probit, and other microeconometric models. | Econometrics and Data Analysis | 4 |
| Core Subtotal: | 24 units |
APPROVED ELECTIVES
Minimum of 21 units from the following:
| Course Number & Description | Course Title | Units |
|---|---|---|
| GSB 501 Advanced individual research planned and completed under the direction of a member of the college faculty. Designed to meet the needs of qualified students who wish to pursue investigations which cannot be followed effectively in regularly offered elective courses. A formal written proposal must be accepted by the Associate Dean of OCOB Graduate Programs before work begins. | Individual Research | 1-4 |
| GSB 503 Collaborative business project with a client organization that allows graduate level students the opportunity to apply knowledge, skills and competencies to address a business problem. Small teams work in collaboration with a client organization and a faculty advisor. A formal written proposal must be accepted by the Associate Dean of OCOB Graduate Programs before work begins. The project may last up to one year. | Collaborative Industry Project | 1-8 |
| GSB 510 Principles of data visualization and storytelling. Data visualization tools for different types of data in the context of business analytics. Communication of results for business actionable insights. Software use includes Excel, Tableau and R. | Data Visualization and Communication in Business | 4 |
| GSB 516 Analysis of customer information, using a broad range of tools and techniques including predictive, statistical, and optimization models. Integration of data into reporting platforms. Application of findings to marketing decision-making. | Strategic Marketing Analytics | 4 |
| GSB 517 Application of business analytics approaches and techniques to understanding and managing human resources. Emphasizes problems addressed using people analytics, including which methods are best and under what conditions, data quality and validity issues, and interpretation in the HR context. | Strategic People Analytics | 4 |
| GSB 521 Apply cloud resources for business analytics. Identify business benefits of cloud computing, storage, networking, data management and security. Use web services to analyze big data including query, statistical analysis, machine learning and visualization. | Cloud Services & Applications for Business Analytics | 4 |
| GSB 536 Examination of ethical risks raised by data analysis, including data collection, ownership and usage. Philosophical examination of topics raised by data analysis, including consent, privacy, transparency, bias and potential harms from data collection and use. | Data Ethics for Business Analytics | 2 |
| GSB 545 Use of computers for advanced machine learning in business analytics. Topics include boosting, ensemble learning, Bayesian methods, and various types of neural networks. Course may be offered in classroom-based, online, or hybrid format. | Advanced Machine Learning for Business Analytics | 4 |
| GSB 550 Introduction to Bayesian econometrics with a focus on business decision making. Making appropriate use of prior information; computation of posterior densities; Bayesian forecasting and policy evaluation; model selection and diagnostic tools; alternative loss functions tailored to specific business applications. | Bayesian Econometrics | 4 |
| GSB 551 Monte Carlo simulation. Decision making under uncertainty. Linear and non-linear programming. Dynamic models of growth and arrivals. Model risk. Applications to finance, operations, strategic planning, and marketing. | Prescriptive Analytics | 4 |
| GSB 570 Directed group study of selected topics for advanced students. Total credit limited to 8 units. The Class Schedule will list topic selected. | Selected Advanced Topics | 1-4 |
| GSB 575 Career development and preparation with specific focus on the impact of organizational structures on the professions of business analytics and data science. Personal marketing in a dynamic technological environment. | Career Readiness in Data Analytics | 1 |
| Elective Subtotal (minimum): | 21 units |
For more details about the courses, see the Cal Poly catalog.
