这篇博客介绍了适用于中国研究人员和学生的在线课程。

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A question!  Advancements in artificial intelligence (AI) have permeated a wide range of scientific fields, from data, photo, and video processing to problem-solving in the physical realm. Have AI tools not made significant strides towards enhancing modeling accuracy and reducing uncertainty? In light of the existence of AI tools, should we continue to rely on probabilistic methods, such as the Monte Carlo Sampling (MCS) method? The Answer!  This question is …

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Why is it important to learn Monte Carlo Sampling (MCS)? In academic and industrial settings, individuals often rely on algorithms, methods, and specialized software simulations to address work and research-related problems. However, these solution methods typically have a common characteristic - they are deterministic in nature. This means that they do not account for uncertainty or margin of error, leading to potential flaws in the results and raising doubts about …

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