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所在平台: Udemy |
课程主页: https://www.udemy.com/course/math-for-data-sciencedata-analysis-and-python-programming/
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课程名称：数据科学、数据分析与机器学习的数学 课程概述：本课程将学习数据科学、数据分析和机器学习所需的数学基础知识。我们将讨论线性代数、统计学与概率、微积分和几何在这些技术领域中的重要性。由于数据科学的学习者包括工程师和商业学生，因此本课程旨在同时适合初学者和进阶学习者。此外，课程对于计算机科学/人工智能的学生以及学习Python编程的学员同样有益。 课程内容涵盖以下领域： 1. 线性代数的重要性 - 矩阵的类型及其性质 - 矩阵的加法与乘法 - 矩阵的转置性质 - 特征值与特征向量 - 高斯消元法求解线性方程组 - Cayley-Hamilton 定理 2. 统计学在数据科学中的重要性 - 统计学：简介 - 数据分类与测量尺度 - 集中趋势的量度 - 离散程度的量度 - 概率基础知识 3. 微积分对数据科学的重要性 - 函数、极限和连续性的基本概念 - 导数及其计算 - 极值和弹性分析 4. 欧几里得几何的重要性 - 几何基础概念 - 集合论的定义与表示 - 实值函数的图形 每个主题都将有简单的概念解释，并辅以选定的示例，旨在为学生打下坚实的基础，帮助他们备考竞争性测试和深入学习高等数学。课程中还将提供问答支持，且会根据学员反馈更新课件内容。希望本课程能够提升学生的理解能力和自信心，期待你们加入课程！快来报名吧！
In this course, we will learn Math essentials for Data science,Data analysis and Machine Learning. We will also discuss the importance of Linear Algebra,Statistics and Probability,Calculus and Geometry in these technological areas. Since data science is studied by both the engineers and commerce students ,this course is designed in such a way that it is useful for both beginners as well as for advanced level. The lessons of the course is also beneficial for the students of Computer science /artificial intelligence and those learning Python programming.Here, this course covers the following areas:Importance of Linear AlgebraTypes of MatricesAddition of Matrices and its PropertiesMatrix multiplication and its PropertiesProperties of Transpose of MatricesHermitian and Skew Hermitian MatricesDeterminants ; IntroductionMinors and Co factors in a DeterminantProperties of DeterminantsDifferentiation of a DeterminantRank of a MatrixEchelon form and its PropertiesEigenvalues and EigenvectorsGaussian Elimination Method for finding out solution of linear equationsCayley Hamilton TheoremImportance of Statistics for Data ScienceStatistics: An IntroductionStatistical Data and its measurement scalesClassification of DataMeasures of Central TendencyMeasures of Dispersion: Range, Mean Deviation, Std. Deviation & Quartile DeviationBasic Concepts of ProbabilitySample Space and Verbal description & Equivalent Set NotationsTypes of Events and Addition Theorem of ProbabilityConditional ProbabilityTotal Probability TheoremBaye's TheoremImportance of Calculus for Data science Basic Concepts: Functions, Limits and ContinuityDerivative of a Function and Formulae of DifferentiationDifferentiation of functions in Parametric FormRolle;s TheoremLagrange's Mean Value TheoremAverage and Marginal ConceptsConcepts of Maxima and MinimaElasticity: Price elasticity of supply and demandImportance of Euclidean GeometryIntroduction to GeometrySome useful Terms,Concepts,Results and FormulaeSet Theory: Definition and its representationType of SetsSubset,Power set and Universal setIntervals as subset of 'R'Venn DiagramsLaws of Algebra of SetsImportant formulae of no. of elements in setsBasic Concepts of FunctionsGraphs of real valued functionsGraphs of Exponential , Logarithmic and Reciprocal FunctionsEach of the above topics has a simple explanation of concepts and supported by selected examples. I am sure that this course will be create a strong platform for students and those who are planning for appearing in competitive tests and studying higher Mathematics.You will also get a good support in Q & A section. It is also planned that based on your feed back, new course materials will be added to the course. Hope the course will develop better understanding and boost the self confidence of the students.Waiting for you inside the course! So hurry up and Join now!!
