California Polytechnic State University, Pomona

What you'll study

The programme covers foundational and applied topics rather than listing discrete named electives in the source. Core subject areas referenced include:

• Databases — principles for storing and managing organizational data.
• Statistics and predictive/prescriptive modeling — statistical techniques and models used to forecast and optimize decisions.
• Optimization and decision theories — methods for improving decisions under constraints.
• Machine learning — practical ML approaches for business problems.
• Programming and data tools — SQL and Python or R for analysis and implementation.
• Natural language processing and Big Data — techniques for unstructured text and large-scale datasets.

Entry requirements

The source page does not provide specific admissions criteria. Prospective applicants should consult the programme's admissions page for official prerequisites, application materials and deadlines.

Career prospects

The programme describes a range of analytic and technology leadership roles students commonly pursue, including:

• Chief Technology Officer (CTO)
• Data Architect
• Data Engineer
• Predictive Modeling Analyst
• Business Intelligence Engineer
• Customer Analytics Director
• Statistician
• Big Data Consultant
• Technology Consultant
• Chief Data Officer (CDO)
• Senior Quantitative Developer

Scholarships & funding angle (general)

The source references financial information broadly but does not list specific funding options. Applicants should explore the university's financial aid, departmental scholarships and external fellowships; many graduate programmes also provide assistantships or industry partnerships—check the programme and university financial-aid pages for current opportunities.