AI for Business Decision Making equips managers and executives with practical, non-technical skills to lead AI-driven decisions across the enterprise. You’ll learn how supervised, unsupervised, and reinforcement learning improve decision accuracy; how to prepare data and engineer features; and how to train, validate, and integrate models into existing workflows and systems via APIs and automation. Through guided, hands-on notebooks, you’ll experiment with predictive analytics, Natural Language Processing (including sentiment analysis), and Large Language Models (LLMs) for real executive use cases—from customer feedback to process optimization and risk prediction. The course also covers governance and ethics (privacy, security, bias, explainability), human-in-the-loop design, and measuring business impact. Advanced topics introduce genetic/evolutionary methods and long-term reward optimization with reinforcement learning to inform strategy and planning. By the end, you’ll be able to select the right technique for a decision problem, evaluate model reliability, integrate AI into business processes, and build an actionable roadmap for sustainable, responsible AI adoption.