Hybrid AI for Business Program Curriculum

This course provides a comprehensive overview of generative AI technologies, advanced experience in prompt engineering, and their application in business contexts. Students will explore various generative AI platforms, understand their capabilities, and learn practical methods for leveraging these tools to solve business problems. The course emphasizes hands-on experience with different AI platforms, enabling students to develop skills that are directly applicable to their professional careers.

This advanced course offers a deep dive into cutting-edge artificial intelligence (AI) techniques, with a specific focus on prompt engineering as a pivotal tool for driving AI-powered business transformation. Students will gain a comprehensive understanding of prompt engineering methodologies, enabling them to optimize and control the behavior of AI models across a variety of business contexts. The course blends theoretical understanding with hands-on application, equipping students with the practical skills needed to design, optimize, and implement AI-driven solutions in real-world business scenarios. Students will work with cutting-edge AI platforms and tools, applying the latest prompt engineering techniques to solve business challenges across industries. By the end of the course, students will be prepared to lead AI initiatives within their organizations, with the ability to leverage advanced AI technologies to drive innovation, efficiency, and decision-making.

This course offers in-depth coverage of advanced concepts and techniques in artificial intelligence. Students will gain a deep understanding of AI technologies, including machine learning and deep learning, and their real-world applications across various industries. Through case studies in computer vision, natural language processing and Internet of Things, and through hands-on projects, students will learn to craft AI strategies, deploy AI solutions using industry-standard platforms, and navigate the challenges of AI integration in business environments. By the end of the course, students will be equipped to design, implement, and manage AI-driven projects to solve a real business problem.

This capstone course is the culmination of the student’s studies in AI and its applications in modern workflows, designed to synthesize and apply the knowledge and skills acquired throughout the program. As a capstone experience, this course challenges students to integrate Artificial Intelligence (AI) into real-world business processes, demonstrating the ability to lead AI-driven transformations within an organization. Participants will work on a comprehensive project that involves identifying a business problem, designing an AI solution, and implementing that solution into an existing workflow. The course emphasizes practical application, requiring students to navigate the complexities of AI integration, including data acquisition, model development, deployment, and evaluation. Ethical considerations, change management, and the impact of AI on workforce dynamics will also be key components of the course. Upon completion, students will not only have a robust understanding of AI integration but also a portfolio project that showcases their ability to drive innovation and efficiency through AI technologies.

This course explores descriptive analytics tools and techniques across various business scenarios, beginning with traditional methods to answer, "What happened?" Students will acquire, clean, manipulate, and visualize business data using spreadsheets and programming. As the course progresses, students apply advanced statistical techniques like descriptive measures, sampling, estimation, and inference. The course concludes with a transition to predictive analytics, focusing on linear and multiple regression to uncover relationships in business data.

This course covers predictive analytics tools and techniques for addressing a variety of business challenges, starting with regression and forecasting to answer, "What will happen in the future?" Students analyze data from business contexts and explore software for handling big data. The course also delves into advanced topics like data mining, text, and social media analytics. It concludes with an overview of AI and machine learning concepts, such as neural networks, to help students enhance their organizations' analytics capabilities. Software and applications evolve with technological advances and instructor focus.

BAN 850 focuses on prescriptive analytics methods for business decision-making and risk mitigation, particularly in supply-side processes. Early in the course, students learn prescriptive analytics tools and techniques. Later, the emphasis shifts to applying these methods in areas like supply chain, service management, operations, logistics, and transportation. The course adapts to reflect emerging theory, practice, and instructor interests.

This course explores the transformative role of AI in modern organizations, focusing on its impact on organizational structure, culture, roles, collaboration, and workforce dynamics. Students will gain a deep understanding of change management strategies for AI adoption, the evolution of teamwork and collaboration in AI-enhanced environments, human perceptions and attitudes towards AI in the workplace, and the reshaping of organizational structures and roles in the age of AI. Students will master strategies for cultivating trust in AI systems, enhancing organizational AI literacy, creating effective communication of AI integration, and striking an optimal equilibrium between automation and human engagement through improved teamwork.

This foundational course offers an in-depth exploration of AI from a "state of play" perspective, focusing on the maturity life cycle and its application across major functional areas of business. Students will gain practical, hands-on experience in assessing the current state of AI technologies and their strategic impact as well as understanding how to identify and assess evolving trends.