This book complements another book of ours. That book covers an introduction to the foundations of artificial intelligence (AI) in business, with minimal technical jargon. This book focuses on the technical side, yet remains accessible enough for business managers and non-computer science majors. It covers topics including Python, linear algebra, calculus, probability, statistics, problem-solving and search, knowledge representation, reasoning and decision making, and learning in intelligent systems. Each topic is covered in just enough depth to prepare you for your journey to understand the what and why behind courses such as machine learning, deep learning, natural language processing, computer vision, reinforcement learning, and large language models. We believe anyone can learn AI if they put in enough effort and know-how. To support active learning, the book incorporates a variety of pedagogical tools: multiple-choice questions embedded throughout each section to help readers test and reinforce their grasp of key concepts as they progress, and hands-on exercises that connect theoretical concepts directly to real-world business operations and decision-making. Through this balanced approach, readers gain a solid understanding of essential AI prerequisite concepts.
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