COURSE CURRICULUM

The MBA with a Data Analytics (STEM) concentration is designed to integrate core business administration training with advanced quantitative and computational methods for evidence-based decision-making in modern organizations. Students begin with a foundation core in accounting, economics, and finance (4.5 credits), followed by a 25-credit MBA core that builds managerial competence in areas such as managerial accounting, corporate finance, global economics, marketing analysis, leadership, organizational change, and strategic management, culminating in a capstone course that synthesizes learning across functional business domains. The Data Analytics concentration then adds a minimum of 15 additional credits focused on developing technical expertise in data-driven problem solving, reflecting the increasing importance of big data, machine learning, and statistical modeling in business environments. Required courses in the concentration include Data Mining for Business Intelligence, Business Forecasting, and Knowledge Management, which collectively emphasize identifying patterns in organizational data, predicting future trends, and applying information systems to support strategic decision-making. Students then select additional electives from a broad set of analytics-oriented courses spanning business analytics, finance, marketing, operations, and information systems, including topics such as supervised and unsupervised machine learning, data visualization, database management, econometrics, Power BI dashboarding, supply chain analytics, and marketing analytics, allowing customization toward specific industry applications. A defining feature of the concentration is its emphasis on technical tools and programming, particularly the R language, which is used for statistical computing and data analysis across multiple business functions. The program is STEM-designated, which highlights its strong quantitative focus and its alignment with computational and analytical skill development needed in data-intensive industries. In addition, students may apply up to three credits of internship experience toward the concentration, providing applied exposure to real-world datasets and business environments. Overall, the structure prepares graduates to interpret complex datasets, build predictive models, and translate analytical results into actionable business strategies across finance, marketing, operations, and management contexts, positioning them for roles in business analytics, consulting, financial analysis, and data-driven decision-making leadership.