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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/integral-calculus-and-numerical-analysis-for-data-science
课程评论：没有评论
课程名称：数据科学中的积分微积分与数值分析 概述：您对数据科学感兴趣，但缺乏相关的数学背景吗？数学一直是您避之不及的难题吗？本课程将为您提供对基础积分微积分的直观理解，包括分部积分、曲线下的面积和积分计算。课程还将涵盖根寻找方法、矩阵分解和偏导数的相关内容。该课程旨在为学习者成功完成数据科学应用中的统计建模课程做好准备，该课程是科罗拉多大学博尔德分校数据科学硕士（MS-DS）项目的一部分。 课程大纲： 1. 曲线下的面积 - 描述：探索曲线下的面积的概念，其与积分的关系，并计算基本积分。 2. 数值分析简介 - 描述：介绍数值分析，使用两种根寻找方法。 3. 对角化与奇异值分解 - 描述：探索一般矩阵分解以及一种特殊且有用的版本——奇异值分解（SVD）。 4. 偏导数与最速降 descent - 描述：学习一个核心的微积分概念——偏导数，并深入研究方向导数及其在高阶统计中的应用。 通过本课程，您将建立坚实的数学基础，为进一步的数据科学学习做好准备。
Name:Area Under The Curve
Description:Explore the notion of area under a curve, how that relates to the integral and compute basic integrals.
Name:Numerical Analysis Intro
Description:Introduction to Numerical Analysis using 2 root-finding methods.
Name:Diagonalization & SVD
Description:Explore general matrix decomposition, as well as a specialized and useful version called Singular Value Decomposition.
Name:Partial Derivatives & Steepest Descent
Description:We will learn a core calculus concept called partial derivatives, as well as delving into directional derivatives and their usefulness in higher level statistics.
Are you interested in Data Science but lack the math background for it? Has math always been a tough subject that you tend to avoid? This course will provide an intuitive understanding of foundational integral calculus, including integration by parts, area under a curve, and integral computation. It will also cover root-finding methods, matrix decomposition, and partial derivatives. This course is designed to prepare learners to successfully complete Statistical Modeling for Data Science Application, which is part of CU Boulder's Master of Science in Data Science (MS-DS) program. Logo courtesy of ThisisEngineering RAEng on Unsplash.com
