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Inhaltsangabe
Volume II continues the journey from competent programming to independent practice and intelligent systems. It opens the world beyond a single file - networks, APIs, databases, automation, visualisation, and deployment - and then turns Python and AI into partners in learning and problem solving. Across Chapters 52-100 you will build web and data applications, negotiate HTTP, JSON, and APIs, manage data stores, automate workflows, and apply Python to science, computation, and machine learning. You will learn to use AI as a tutor, collaborator, critical reviewer, and pair programmer - always within declared boundaries and with verification as the final authority. Every chapter begins with purpose, boundary, contents, learning aims, and reasons for care. You will predict, test, inspect, and explain. You will keep the smallest test that can change your mind. You will treat elegant explanations as proposals until evidence confirms them. Write the prediction. Run the test. Earn the result.
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Über die Autorin bzw. den Autor
Richard Murdoch Montgomery, MD, PhD, is a physician, neurologist, and mathematician whose work ranges across clinical neuroscience, mathematical sciences, computing, economics, and the history and philosophy of science. He is the author of more than one hundred scientific and technical books published through the Scottish Science Society, including extended treatises on scientific and financial calculators, graduate mathematics, artificial intelligence, data science, physics, biology, medicine, and intellectual history by The Scottish Science Society. His books favour derivation, practical method, and conceptual continuity over abbreviated instruction or itemisation. A result is not merely displayed; it is earned, tested, and placed within the argument that gives it meaning. This combination of clinical experience, mathematical discipline, and long-form scholarship informs both his teaching and his writing.
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Learning Python with Artificial Intelligence
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