Applied Data Science and AI: Information Management for Engineering and Business Intelligence

Data Science and Artificial Intelligence (AI) are increasingly vital in aiding managers to comprehend the influence of Information Systems (IS) on decision-making, especially amid the advancements in cloud and quantum computing. This text emerges from discussions in the Engineering and Business Management fields, addressing the educational requirements of students, engineers, and industry managers engaging in complex decision-making. 

In today's digital era, students and practitioners, often termed digital natives, are familiar with information technologies such as AI, smartphones, and social media. This demographic shift necessitates novel approaches to education in engineering and management, particularly concerning Generative and Agentic AI. Modern learners expect workplace tools to reflect the capabilities they encounter in personal settings, thus impacting organizational practices and expectations. It becomes increasingly important for engineers and managers to capitalize on their technology proficiency. 

The text also tackles significant challenges associated with managing AI and the vast amount of data generated by organizational operations, customer interactions, and the evolving AI landscape. It is crucial for engineers and managers to critically analyze this information and engage in discussions about its implications. To address these needs, the book is divided into 20 comprehensive chapters that encompass topics like AI, data science, data management, optimization, and the integration of both technical and business knowledge. 

Key sections delve into complex relationships concerning data governance, data science algorithms, IS, and decision-making strategies pertinent in the AI and data-driven insights revolution. It covers fundamental subjects including convex optimization, Monte Carlo simulation, and both supervised and unsupervised machine learning within the context of advancing generative and agentic AI. Recognizing the ever-evolving landscape of Engineering and Management, the text aims to impart foundational insights that guide engineers and managers through continuous technological advancements, empowering them with data-informed decision-making skills. By emphasizing contemporary business and engineering environments, as AI emerges as a pivotal element driving productivity, innovation, and disruption, it encourages active engagement from students and faculty with current materials and discussions to maintain the dynamism of learning relevant to real-world applications