Master of Science in Technology Management: Business Analytics

BU 601 focuses on understanding and managing individual and group behavior in organizations, stress management and well-being, and ethical responsibilities in business. The course explores the organizational behavior model, diversity's role in interpersonal interactions, and job satisfaction measurement. Students learn about emotions, moods, and the relevance of intellectual and physical abilities. The curriculum covers virtual communication in modern organizations and the negotiation process. It addresses stress management at individual and organizational levels and examines group decision-making strengths and weaknesses. By integrating these topics, the course provides a comprehensive understanding of human behavior in organizational settings, equipping students with essential skills for effective management and ethical leadership in today's dynamic business environment.

OD 655 examines the fundamental role of creativity and innovation in leadership and organizational development. The course connects these concepts to various organizational practices, including human resources programs and organizational development interventions. Students explore the significance of creativity and innovation at individual, team, and organizational levels. The curriculum emphasizes the application of creative and innovative approaches to problem-solving, human resources management, team dynamics, and diversity initiatives. By focusing on these areas, the course aims to enhance organizational effectiveness and adaptability. Students gain proficiency in relevant terminology, concepts, and analytical techniques, preparing them to foster innovation and creativity in their professional roles and contribute to organizational growth and success.

OD 688 provides a comprehensive exploration of leadership theory within the context of management and organizations. The course surveys a broad spectrum of leadership theories and the research underpinning them. Students learn to analyze various models of leadership behavior and effectiveness, understanding both their strengths and limitations. The curriculum examines how organizational structures, followers, and situations influence leadership effectiveness. It also delves into the impact of leadership on change processes within organizations. By the end of the course, students are equipped to compose their own set of guiding principles for leadership development. This approach enables students to apply theoretical knowledge practically, developing their leadership skills and understanding of organizational dynamics.

PM 672 offers a comprehensive overview of project management, focusing on its main components, project metrics, and strategies to improve project success rates. The course explores various project management approaches, including traditional IPECC, agile, and scrum methodologies. Students gain familiarity with key project metrics and learn to perform basic calculations, acquiring practical tools for use in their professional environments. The curriculum emphasizes the critical balance between hard and soft skills essential for project managers' success. It covers interpersonal dynamics, project lifecycle planning, and effective management of project participation, teamwork, and conflict. The course also provides insights into the PMP exam, preparing students for professional certification. This practical approach equips students with the skills needed to navigate complex project environments successfully.

BA 694 BA Capstone for the Master of Science in Technology Management: Business Analytics program, requiring students to complete a faculty-approved project demonstrating professional competence. This 16-week course integrates theoretical knowledge with practical application, allowing students to showcase skills developed throughout their master's program and work experience. The project contributes to relevant discipline literature and is comparable to professional-level work. Students apply theory and practice in their specific discipline, develop a research proposal and literature review, and either apply the action research model or recommend actions based on case study data. This comprehensive project demonstrates students' ability to research, analyze, and apply management theories to real-world scenarios, preparing them for advanced roles in their chosen fields.

BA 695 BA Internship offers a structured learning and work experience in a position approved by the School of Business for graduate credit. This internship course aims to bridge academic knowledge with professional practice, allowing students to apply theoretical concepts in real-world settings. The curriculum focuses on developing essential workplace skills such as problem-solving, teamwork, and effective communication. Students have the opportunity to explore various career paths, gain insights into potential job roles, and build professional networks. The internship enhances employability by providing hands-on experience and specific job-related skills. Through reflective practices and feedback, students engage in personal and professional growth, identifying strengths and areas for improvement. This practical experience prepares students for successful entry into the workforce post-graduation.

BA 600 Foundations of Business Analytics provides a solid grounding in data analytics concepts essential for modern business practices. The curriculum covers the entire analytics pipeline from data acquisition through visualization and statistical analysis using tools like Python, R, and Excel. Key topics include data preprocessing techniques, exploratory data analysis methods, regression analysis fundamentals, hypothesis testing principles, and effective data visualization strategies. By applying critical thinking throughout the analytics process, students learn how to derive actionable insights from complex datasets that inform strategic business decisions.

BA 611 focuses on the principles and practices of business intelligence, emphasizing data analysis and reporting. Students learn to leverage data and analytics tools to create dashboards, scorecards, and reports that facilitate informed decision-making in organizations. The course covers various data analysis and visualization techniques, including OLAP, data mining, and advanced visualization tools. Students develop the skills to analyze and interpret data with business intelligence tools, create effective communication materials, and develop strategies to drive organizational performance. By the end of the course, students can use business intelligence to improve competitive advantage and make data-driven decisions, preparing them for roles that require strategic data analysis and interpretation.

BA 621 provides a comprehensive understanding of optimization and decision models, focusing on mathematical modeling and optimization techniques. Students learn to represent real-world problems using mathematical modeling and apply optimization techniques to find optimal solutions. The course covers linear and nonlinear programming, network optimization, and integer programming. Students gain hands-on experience with popular optimization tools like Gurobi and CPLEX. The curriculum emphasizes developing critical thinking and problem-solving skills through applying optimization and decision models to real-world business problems. Students learn to analyze the strengths and limitations of different optimization techniques and design innovative models to address complex issues, preparing them for roles requiring advanced analytical and decision-making skills.

BA 631 offers a comprehensive exploration of data mining techniques and their business applications. Students learn to extract valuable insights from large datasets using statistical and machine learning algorithms. The course covers various data mining techniques such as clustering, classification, and association rule mining. Students gain proficiency in popular data mining tools like Python, R, and Weka. The curriculum emphasizes evaluating the appropriateness of different algorithms for analyzing large datasets and developing effective data mining workflows. Students learn to assess the effectiveness of data mining techniques and tools through critical analysis and evaluation of results. By the end of the course, students can analyze large datasets to find meaningful patterns that contribute to solving practical organizational problems.

BA 641 provides a comprehensive understanding of marketing and social media analytics and their business applications. Students learn to use data analytics to improve marketing performance and gain insights into consumer behavior. The course covers various marketing analytics techniques, including customer segmentation, customer lifetime value, and marketing mix modeling. Students also gain proficiency in popular social media analytics tools like Facebook Insights, Twitter Analytics, and Google Analytics. The curriculum emphasizes evaluating the effectiveness of data analytics techniques for analyzing marketing performance and consumer behavior. Students learn to identify and analyze changing consumer trends, create competitive advantages, and adapt marketing strategies to effectively reach and engage diverse audiences.

BA 651 offers a comprehensive exploration of financial analytics and their business applications. Students learn to analyze financial data and use analytics tools to gain insights into financial performance. The course covers various financial analytics techniques, including financial modeling, portfolio analysis, and risk management. Students gain proficiency in popular financial analytics tools such as Excel, R, and Python. The curriculum emphasizes evaluating and justifying data-driven strategies for optimal financial decision-making. Students learn to select and apply appropriate analytical techniques to extract insights from financial data, quantify and evaluate the impact of uncertainty on financial models, and critically analyze real-world financial problems. The course prepares students to synthesize complex financial analyses and present actionable recommendations to diverse stakeholders.

CS 661 AI and Machine Learning is a comprehensive course that delves into the core concepts and applications of artificial intelligence (AI) and machine learning (ML). Students gain in-depth knowledge of designing, implementing, and evaluating AI and ML models for intelligent decision-making, pattern recognition, and natural language processing (NLP). The curriculum covers essential topics such as neural networks, deep learning, reinforcement learning, and NLP. Through hands-on experience with tools like TensorFlow and PyTorch, students learn to create neural networks for tasks like image classification. The course emphasizes practical skills, including analyzing model performance using various metrics and evaluating ethical considerations in AI applications. A final project allows students to apply their knowledge to solve real-world problems, preparing them for the challenges of implementing AI and ML in diverse industries.