A manager's job comprises two fundamental tasks: making predictions (e.g., forecasting demand, assessing risks, evaluating candidates) and acting on those predictions (e.g., launching products, making investments, hiring talent). Machine learning is a powerful tool for making predictions - and increasingly, decisions - with data. This course provides students with a high-level understanding of how artificial intelligence and machine learning fit into business strategy. You will learn to identify opportunities and risks in applying AI across various domains - from finance and marketing to operations and human resources. The course covers the major ML paradigms: supervised learning, unsupervised learning, reinforcement learning, and natural language processing including large language models. Through lectures, hands-on exercises (minimal coding required), and mini-case discussions, you will develop the vocabulary and frameworks to evaluate AI-driven solutions, recognize common pitfalls like data bias and interpretability challenges, and understand how ethical considerations must be integrated into strategic decisions.