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商业数据分析特训班
〖课程目录〗:
万门教育 商业数据分析特训班 [25.3G]
┣━━课程 [24.1G]
┃ ┣━━31待定 [8.7G]
┃ ┃ ┣━━31.10Growth hacking-0304.mp4 [283.7M]
┃ ┃ ┣━━31.11Growth hacking-0304.mp4 [8.5M]
┃ ┃ ┣━━31.12MySQL 1 -0305.mp4 [285.2M]
┃ ┃ ┣━━31.13MySQL 1-0305.mp4 [110.9M]
┃ ┃ ┣━━31.14MySQL2 -0306.mp4 [523.9M]
┃ ┃ ┣━━31.15NoSQL Database in Big Data-0307.mp4 [365.4M]
┃ ┃ ┣━━31.16Power BI-0307.mp4 [71.6M]
┃ ┃ ┣━━31.17E-Commerce-0309.mp4 [360.2M]
┃ ┃ ┣━━31.18E-Commerce-0310.mp4 [270.3M]
┃ ┃ ┣━━31.19Gaming Analytics-0312.mp4 [307.9M]
┃ ┃ ┣━━31.1Classification & Clustering Classification vs. Clustering-0223.mp4 [356.1M]
┃ ┃ ┣━━31.20Gaming Analytics-0314.mp4 [310.8M]
┃ ┃ ┣━━31.21感官分析1-0316.mp4 [293.3M]
┃ ┃ ┣━━31.22感官分析2-0316.mp4 [322.8M]
┃ ┃ ┣━━31.23感官分析3-0317.mp4 [329.3M]
┃ ┃ ┣━━31.24感官分析4-0317.mp4 [294.6M]
┃ ┃ ┣━━31.25A-B Testing-0319.mp4 [343.9M]
┃ ┃ ┣━━31.26A-B Testing-0320.mp4 [368.9M]
┃ ┃ ┣━━31.27Capstone-0323.mp4 [459.7M]
┃ ┃ ┣━━31.28Capstone-0324.mp4 [653.7M]
┃ ┃ ┣━━31.2顾客体验Customer Experience-0224.mp4 [271.3M]
┃ ┃ ┣━━31.3定价Pricing-0225.mp4 [268.4M]
┃ ┃ ┣━━31.4SPSS与问卷分析-0226.mp4 [492.7M]
┃ ┃ ┣━━31.5市场研究的基础知识-0227.mp4 [302M]
┃ ┃ ┣━━31.6市场营销的研究应用-0228.mp4 [258.3M]
┃ ┃ ┣━━31.7CRM & RFM- 0301.mp4 [332.3M]
┃ ┃ ┣━━31.8CRM & RFM -0302.mp4 [390.9M]
┃ ┃ ┗━━31.9新业务开发及销售运营管理-0303.mp4 [294.1M]
┃ ┣━━第 1 讲商业数据分析综述（上） [362M]
┃ ┃ ┣━━1.10数据粒度（四）.mp4 [38.3M]
┃ ┃ ┣━━1.11答疑（二）.mp4 [19.7M]
┃ ┃ ┣━━1.12答疑（三）.mp4 [20.1M]
┃ ┃ ┣━━1.13答疑（四）.mp4 [39.8M]
┃ ┃ ┣━━1.1商业数据分析引入.mp4 [31.8M]
┃ ┃ ┣━━1.2什么是商业数据分析？.mp4 [16.1M]
┃ ┃ ┣━━1.3所需技能.mp4 [48.5M]
┃ ┃ ┣━━1.4基本分析流程及供应链各个环节.mp4 [27.8M]
┃ ┃ ┣━━1.5商业理解.mp4 [24.3M]
┃ ┃ ┣━━1.6答疑（一）.mp4 [24M]
┃ ┃ ┣━━1.7数据粒度（一）.mp4 [25.3M]
┃ ┃ ┣━━1.8数据粒度（二）.mp4 [19.6M]
┃ ┃ ┗━━1.9数据粒度（三）.mp4 [26.7M]
┃ ┣━━第 10 讲Python基础（下） [805.1M]
┃ ┃ ┣━━10.10Zip.mp4 [30.3M]
┃ ┃ ┣━━10.11Mutable，Immutable.mp4 [72.9M]
┃ ┃ ┣━━10.12Traversal Sequence Data Structure.mp4 [35.5M]
┃ ┃ ┣━━10.13函数进阶（一）.mp4 [35.6M]
┃ ┃ ┣━━10.14函数进阶（二）.mp4 [62.8M]
┃ ┃ ┣━━10.15函数也可以传递、Lambda.mp4 [55M]
┃ ┃ ┣━━10.16修饰.mp4 [50.8M]
┃ ┃ ┣━━10.17List Comprehensions（一）.mp4 [52M]
┃ ┃ ┣━━10.18List Comprehensions（二）.mp4 [44.9M]
┃ ┃ ┣━━10.1答疑—strip的功能.mp4 [33.9M]
┃ ┃ ┣━━10.2List（一）.mp4 [41.7M]
┃ ┃ ┣━━10.3List（二）.mp4 [44.3M]
┃ ┃ ┣━━10.4List（三）.mp4 [26.8M]
┃ ┃ ┣━━10.5Tuple.mp4 [47.2M]
┃ ┃ ┣━━10.6Dictionary（一）.mp4 [38.8M]
┃ ┃ ┣━━10.7答疑回顾.mp4 [29.5M]
┃ ┃ ┣━━10.8Dictionary（二）.mp4 [61M]
┃ ┃ ┗━━10.9Set.mp4 [42M]
┃ ┣━━第 11 讲Python进阶和面向对象 [687M]
┃ ┃ ┣━━11.10Advanced Python（三）.mp4 [73.6M]
┃ ┃ ┣━━11.11Advanced Python（四）.mp4 [82.2M]
┃ ┃ ┣━━11.1Modules，Packages，and Programs（一）.mp4 [61.6M]
┃ ┃ ┣━━11.2Modules，Packages，and Programs（二）.mp4 [73.5M]
┃ ┃ ┣━━11.3Python Standard Library.mp4 [90.9M]
┃ ┃ ┣━━11.4Python System（一）.mp4 [35M]
┃ ┃ ┣━━11.5Python System（二）.mp4 [63.4M]
┃ ┃ ┣━━11.6Python System（三）.mp4 [71.8M]
┃ ┃ ┣━━11.7Python System（四）.mp4 [21.3M]
┃ ┃ ┣━━11.8Advanced Python（一）.mp4 [59.3M]
┃ ┃ ┗━━11.9Advanced Python（二）.mp4 [54.4M]
┃ ┣━━第 12 讲网络数据获取 [1.7G]
┃ ┃ ┣━━12.10Crawl—BOSS直聘（四）.mp4 [184.7M]
┃ ┃ ┣━━12.11Crawl—BOSS直聘（五）.mp4 [194.2M]
┃ ┃ ┣━━12.12Crawl—BOSS直聘（六）.mp4 [130.1M]
┃ ┃ ┣━━12.13作业：英雄列表整合（一）.mp4 [119.9M]
┃ ┃ ┣━━12.14作业：英雄列表整合（二）.mp4 [123M]
┃ ┃ ┣━━12.15作业：英雄列表整合（三）.mp4 [192.2M]
┃ ┃ ┣━━12.1计算机网络基础.mp4 [28.9M]
┃ ┃ ┣━━12.2网站.mp4 [26.2M]
┃ ┃ ┣━━12.3示例分析.mp4 [165.1M]
┃ ┃ ┣━━12.4知识回顾及预习.mp4 [74.8M]
┃ ┃ ┣━━12.5HTML，CSS，Browser（一）.mp4 [61.9M]
┃ ┃ ┣━━12.6HTML，CSS，Browser（二）.mp4 [52.2M]
┃ ┃ ┣━━12.7Crawl—BOSS直聘（一）.mp4 [90.9M]
┃ ┃ ┣━━12.8Crawl—BOSS直聘（二）.mp4 [194.6M]
┃ ┃ ┗━━12.9Crawl—BOSS直聘（三）.mp4 [78M]
┃ ┣━━第 13 讲概率论基本概念 [165.3M]
┃ ┃ ┣━━13.1课程简述及小测试.mp4 [20.6M]
┃ ┃ ┣━━13.2自然科学vs数学.mp4 [14.8M]
┃ ┃ ┣━━13.3随机试验.mp4 [17.9M]
┃ ┃ ┣━━13.4古典概型（一）.mp4 [11.8M]
┃ ┃ ┣━━13.5古典概型（二）.mp4 [24.2M]
┃ ┃ ┣━━13.6条件概率.mp4 [18.1M]
┃ ┃ ┣━━13.7贝叶斯公式（一）.mp4 [18M]
┃ ┃ ┣━━13.8贝叶斯公式（二）.mp4 [18.4M]
┃ ┃ ┗━━13.9独立性.mp4 [21.6M]
┃ ┣━━第 14 讲随机变量及其分布（上） [172.1M]
┃ ┃ ┣━━14.1随机变量.mp4 [19.7M]
┃ ┃ ┣━━14.20-1分布和伯努利实验（一）.mp4 [14.3M]
┃ ┃ ┣━━14.3伯努利实验例题讲解（一）.mp4 [33.3M]
┃ ┃ ┣━━14.4伯努利实验例题讲解（二）.mp4 [14M]
┃ ┃ ┣━━14.5随机变量分布函数（一）.mp4 [20.8M]
┃ ┃ ┣━━14.6随机变量分布函数（二）.mp4 [19.8M]
┃ ┃ ┣━━14.7随机变量分布函数（三）.mp4 [18.5M]
┃ ┃ ┣━━14.8随机变量分布函数（四）.mp4 [10.2M]
┃ ┃ ┗━━14.9随机变量分布函数（五）.mp4 [21.4M]
┃ ┣━━第 15 讲随机变量及其分布（下） [157.9M]
┃ ┃ ┣━━15.10正态分布例题讲解（三）.mp4 [12.3M]
┃ ┃ ┣━━15.1分布函数例题及贝叶斯公式回顾.mp4 [21.6M]
┃ ┃ ┣━━15.2贝叶斯公式例题（一）.mp4 [17.8M]
┃ ┃ ┣━━15.3贝叶斯公式例题（二）.mp4 [24.1M]
┃ ┃ ┣━━15.4贝叶斯定理思想归纳.mp4 [16.1M]
┃ ┃ ┣━━15.5贝叶斯定理应用总结及分布函数.mp4 [10.9M]
┃ ┃ ┣━━15.6正态分布例题讲解（一）.mp4 [20.2M]
┃ ┃ ┣━━15.7正态分布例题讲解（二）.mp4 [10.1M]
┃ ┃ ┣━━15.8离散型分布函数.mp4 [8.4M]
┃ ┃ ┗━━15.9连续型分布函数.mp4 [16.4M]
┃ ┣━━第 16 讲随机变量的数字特征 [129.8M]
┃ ┃ ┣━━16.1离散型分布函数的数学期望.mp4 [14.8M]
┃ ┃ ┣━━16.2连续型分布函数的数学期望.mp4 [10.6M]
┃ ┃ ┣━━16.3例题讲解（一）.mp4 [19.9M]
┃ ┃ ┣━━16.4例题讲解（二）.mp4 [18.1M]
┃ ┃ ┣━━16.5例题讲解（三）.mp4 [17M]
┃ ┃ ┣━━16.6正态分布的标准差定义.mp4 [13.9M]
┃ ┃ ┣━━16.7数学期望及例题讲解.mp4 [19.8M]
┃ ┃ ┗━━16.8方差及例题讲解.mp4 [15.7M]
┃ ┣━━第 17 讲多维随机变量 [213.7M]
┃ ┃ ┣━━17.1二维随机变量（一）.mp4 [21.6M]
┃ ┃ ┣━━17.2二维随机变量（二）.mp4 [22.1M]
┃ ┃ ┣━━17.3二维随机变量（三）.mp4 [21.1M]
┃ ┃ ┣━━17.4N维随机变量（一）.mp4 [10.8M]
┃ ┃ ┣━━17.5N维随机变量（二）.mp4 [17.3M]
┃ ┃ ┣━━17.6中心极限定理（一）.mp4 [16M]
┃ ┃ ┣━━17.7中心极限定理（二）.mp4 [22.1M]
┃ ┃ ┣━━17.8随机样本与箱线图.mp4 [17.2M]
┃ ┃ ┗━━17.9SPSS数据分析.mp4 [65.5M]
┃ ┣━━第 18 讲数理统计及SPSS应用 [634.5M]
┃ ┃ ┣━━18.10单因素方差分析（二）.mp4 [70.8M]
┃ ┃ ┣━━18.11两因素方差分析.mp4 [72.9M]
┃ ┃ ┣━━18.12卡方检验（一）.mp4 [41.1M]
┃ ┃ ┣━━18.13卡方检验（二）.mp4 [29.2M]
┃ ┃ ┣━━18.14卡方检验（三）.mp4 [28.6M]
┃ ┃ ┣━━18.15简单线性回归（一）.mp4 [41.7M]
┃ ┃ ┣━━18.16简单线性回归（二）.mp4 [41.5M]
┃ ┃ ┣━━18.1T检验理论推导和前提.mp4 [13.4M]
┃ ┃ ┣━━18.2单样本t检验（一）.mp4 [38.7M]
┃ ┃ ┣━━18.3单样本t检验（二）.mp4 [62.3M]
┃ ┃ ┣━━18.4独立样本t检验（一）.mp4 [32.5M]
┃ ┃ ┣━━18.5独立样本t检验（二）.mp4 [38.4M]
┃ ┃ ┣━━18.6配对样本t检验（一）.mp4 [37.8M]
┃ ┃ ┣━━18.7配对样本t检验（二）.mp4 [25.7M]
┃ ┃ ┣━━18.8方差分析.mp4 [14.6M]
┃ ┃ ┗━━18.9单因素方差分析（一）.mp4 [45.2M]
┃ ┣━━第 19 讲Python NumPy，Pandas [619.1M]
┃ ┃ ┣━━19.10统计、排序和存储array.mp4 [40.2M]
┃ ┃ ┣━━19.11Pandas简单介绍和Series.mp4 [49.3M]
┃ ┃ ┣━━19.12Series.mp4 [38.6M]
┃ ┃ ┣━━19.13DataFrame.mp4 [24.9M]
┃ ┃ ┣━━19.14Titanic example.mp4 [36.3M]
┃ ┃ ┣━━19.15Index object、Reindex.mp4 [14.4M]
┃ ┃ ┣━━19.16Drop Data、Slice Data.mp4 [22.9M]
┃ ┃ ┣━━19.17Data Alignment、Rank and Sort.mp4 [26.6M]
┃ ┃ ┣━━19.1NumPy简单介绍.mp4 [131.5M]
┃ ┃ ┣━━19.2创建矩阵（一）.mp4 [39M]
┃ ┃ ┣━━19.3创建矩阵（二）.mp4 [21.9M]
┃ ┃ ┣━━19.4算术操作和矩阵计算.mp4 [22.9M]
┃ ┃ ┣━━19.5Several Useful Operations.mp4 [23.6M]
┃ ┃ ┣━━19.6一维矩阵.mp4 [34.1M]
┃ ┃ ┣━━19.7多维矩阵（一）.mp4 [31.6M]
┃ ┃ ┣━━19.8多维矩阵（二）.mp4 [39.6M]
┃ ┃ ┗━━19.9Generate Grid、NumPy where function.mp4 [21.9M]
┃ ┣━━第 2 讲商业数据分析综述（下） [253.7M]
┃ ┃ ┣━━2.1数据质量与形式.mp4 [52.9M]
┃ ┃ ┣━━2.2数据隐性.mp4 [32.4M]
┃ ┃ ┣━━2.3案例分析.mp4 [32.8M]
┃ ┃ ┣━━2.4不同类型的分析.mp4 [24.3M]
┃ ┃ ┣━━2.5数据可视化.mp4 [72M]
┃ ┃ ┣━━2.6典型数据驱动开发团队的人员.mp4 [27M]
┃ ┃ ┗━━2.7答疑.mp4 [12.3M]
┃ ┣━━第 20 讲Matplotlib, Seaborn [781.3M]
┃ ┃ ┣━━20.10Data-ink ratio举例（一）.mp4 [42.7M]
┃ ┃ ┣━━20.11Data-ink ratio举例（二）.mp4 [68.4M]
┃ ┃ ┣━━20.12Seaborn：Regression plot.mp4 [28.4M]
┃ ┃ ┣━━20.13Bar plot、FacetGrid.mp4 [69.3M]
┃ ┃ ┣━━20.14Pair Plot、Joint Plot与Line Plot.mp4 [40.1M]
┃ ┃ ┣━━20.15Plotly（一）.mp4 [55.6M]
┃ ┃ ┣━━20.16Plotly（二）.mp4 [63.6M]
┃ ┃ ┣━━20.1数据可视化引入（一）.mp4 [142.8M]
┃ ┃ ┣━━20.2数据可视化引入（二）.mp4 [73.5M]
┃ ┃ ┣━━20.3什么是Data Visualization.mp4 [35.7M]
┃ ┃ ┣━━20.4Matplotlib简单介绍.mp4 [16.9M]
┃ ┃ ┣━━20.5Data-ink ratio.mp4 [16.8M]
┃ ┃ ┣━━20.6一次性画图和重复性画图的关系.mp4 [28.4M]
┃ ┃ ┣━━20.7Matplotlib及其元素.mp4 [38M]
┃ ┃ ┣━━20.8Mode.mp4 [26.3M]
┃ ┃ ┗━━20.9Basic elements及画图介绍.mp4 [34.7M]
┃ ┣━━第 21 讲Excel数据透视表 [396.5M]
┃ ┃ ┣━━21.10切片器连接多个数据透视表.mp4 [30.1M]
┃ ┃ ┣━━21.11分组.mp4 [42.4M]
┃ ┃ ┣━━21.12设置数值计算方式与自定义计算项.mp4 [39.8M]
┃ ┃ ┣━━21.13例题练习.mp4 [34.3M]
┃ ┃ ┣━━21.1数据透视表课程引入.mp4 [23.5M]
┃ ┃ ┣━━21.2观察数据及创建数据透视表.mp4 [39.3M]
┃ ┃ ┣━━21.3透视表简单练习.mp4 [16.6M]
┃ ┃ ┣━━21.4如何设置数据透视表的格式、风格.mp4 [30.5M]
┃ ┃ ┣━━21.5报表布局、分类汇总、总计.mp4 [32.3M]
┃ ┃ ┣━━21.6排序与筛选（一）.mp4 [37.2M]
┃ ┃ ┣━━21.7排序与筛选（二）.mp4 [17.6M]
┃ ┃ ┣━━21.8刷新、更改数据源.mp4 [24.8M]
┃ ┃ ┗━━21.9切片器操作及简单练习.mp4 [28M]
┃ ┣━━第 22 讲数据可视化 [428.6M]
┃ ┃ ┣━━22.10饼状图答疑.mp4 [6.9M]
┃ ┃ ┣━━22.11练习（一）.mp4 [47M]
┃ ┃ ┣━━22.12练习（二）.mp4 [28.7M]
┃ ┃ ┣━━22.13练习（三）.mp4 [21.5M]
┃ ┃ ┣━━22.14练习（四）.mp4 [28.3M]
┃ ┃ ┣━━22.15练习（五）.mp4 [37.6M]
┃ ┃ ┣━━22.1课前回顾.mp4 [24.2M]
┃ ┃ ┣━━22.2柱状图（一）.mp4 [30.1M]
┃ ┃ ┣━━22.3柱状图（二）.mp4 [36.9M]
┃ ┃ ┣━━22.4柱状图（三）.mp4 [22.7M]
┃ ┃ ┣━━22.5柱状图（四）.mp4 [25.6M]
┃ ┃ ┣━━22.6饼状图、线状图.mp4 [47.5M]
┃ ┃ ┣━━22.7图表结合.mp4 [19.3M]
┃ ┃ ┣━━22.8数据透视图（一）.mp4 [27.7M]
┃ ┃ ┗━━22.9数据透视图（二）.mp4 [24.7M]
┃ ┣━━第 23 讲数据仪表盘Excel Dashboard [436.2M]
┃ ┃ ┣━━23.10创建Dashboard（一）.mp4 [30.6M]
┃ ┃ ┣━━23.11创建Dashboard（二）.mp4 [37.9M]
┃ ┃ ┣━━23.12创建Dashboard（三）.mp4 [24.6M]
┃ ┃ ┣━━23.13课程内容回顾（一）.mp4 [31.8M]
┃ ┃ ┣━━23.14课程内容回顾（二）.mp4 [34.9M]
┃ ┃ ┣━━23.1课前回顾.mp4 [21.8M]
┃ ┃ ┣━━23.2mini图和时间轴.mp4 [32.1M]
┃ ┃ ┣━━23.3数据仪表盘示例及创建仪表盘的步骤.mp4 [27.1M]
┃ ┃ ┣━━23.4创建仪表盘的注意事项与演示.mp4 [17.3M]
┃ ┃ ┣━━23.5创建数据仪表盘：观察整理数据.mp4 [33M]
┃ ┃ ┣━━23.6建立数据透视表和图表（一）.mp4 [24.1M]
┃ ┃ ┣━━23.7建立数据透视表和图表（二）.mp4 [33.9M]
┃ ┃ ┣━━23.8建立数据透视表和图表（三）.mp4 [45.7M]
┃ ┃ ┗━━23.9建立数据透视表和图表（四）.mp4 [41.3M]
┃ ┣━━第 24 讲商业流程综述Business Process [535M]
┃ ┃ ┣━━24.10金融数据分析与人力资源数据分析.mp4 [44.9M]
┃ ┃ ┣━━24.11医疗健康数据分析.mp4 [35.2M]
┃ ┃ ┣━━24.12供应链数据分析与体育数据分析.mp4 [34.8M]
┃ ┃ ┣━━24.13互联网数据分析.mp4 [20.6M]
┃ ┃ ┣━━24.14数据清理—数据分析前必不可少的步骤.mp4 [22.6M]
┃ ┃ ┣━━24.15Case 1：数据质量控制（一）.mp4 [33.4M]
┃ ┃ ┣━━24.16Case 1：数据质量控制（二）.mp4 [19.7M]
┃ ┃ ┣━━24.17数据分析流程及分类.mp4 [26.5M]
┃ ┃ ┣━━24.18描述性、预测性、指导性数据分析.mp4 [18.1M]
┃ ┃ ┣━━24.19Case 2：如何使用数据解答商业问题.mp4 [45.8M]
┃ ┃ ┣━━24.1商业数据分析的驱动力.mp4 [34.8M]
┃ ┃ ┣━━24.20答疑及大数据简述.mp4 [9.6M]
┃ ┃ ┣━━24.2什么是商业数据分析（一）.mp4 [32.2M]
┃ ┃ ┣━━24.3什么是商业数据分析（二）.mp4 [15.7M]
┃ ┃ ┣━━24.4不同部门的应用场景及流程综述.mp4 [35.6M]
┃ ┃ ┣━━24.5市场推广数据分析（一）.mp4 [18.8M]
┃ ┃ ┣━━24.6市场推广数据分析（二）.mp4 [18.7M]
┃ ┃ ┣━━24.7新业务开发.mp4 [19.2M]
┃ ┃ ┣━━24.8销售管理和其他应用场景.mp4 [38.1M]
┃ ┃ ┗━━24.9不同行业的应用场景及答疑.mp4 [10.6M]
┃ ┣━━第 25 讲Marketing Analytics [475.2M]
┃ ┃ ┣━━25.10Marketing Analytics Landscape及答疑.mp4 [29.5M]
┃ ┃ ┣━━25.11Marketing Mix Model.mp4 [26.9M]
┃ ┃ ┣━━25.12MMM模型例题分析.mp4 [30.7M]
┃ ┃ ┣━━25.13市场反应度、线性模型及指数模型.mp4 [23.4M]
┃ ┃ ┣━━25.14Contribution与Optimization.mp4 [28.7M]
┃ ┃ ┣━━25.15Digital Marketing.mp4 [24.7M]
┃ ┃ ┣━━25.16Attribution及举例.mp4 [32.2M]
┃ ┃ ┣━━25.17Linear Attribution及两-模型-较分析.mp4 [13.5M]
┃ ┃ ┣━━25.1市场漏斗模型Marketing Funnel（一）.mp4 [37.6M]
┃ ┃ ┣━━25.2市场漏斗模型Marketing Funnel（二）.mp4 [34.2M]
┃ ┃ ┣━━25.3Samples.mp4 [12.8M]
┃ ┃ ┣━━25.4Marketing vs Marketing Analytics（一）.mp4 [14.7M]
┃ ┃ ┣━━25.5Marketing vs Marketing Analytics（二）.mp4 [44.9M]
┃ ┃ ┣━━25.6Marketing Analytics（一）.mp4 [26.7M]
┃ ┃ ┣━━25.7Marketing Analytics（二）.mp4 [32.2M]
┃ ┃ ┣━━25.8Segmentation及举例.mp4 [40.6M]
┃ ┃ ┗━━25.9Acquisition Model与Analytics Cycle.mp4 [22.2M]
┃ ┣━━第 26 讲市场推广分析Marketing Analytics [249.4M]
┃ ┃ ┣━━26.1ROI—投资回报率.mp4 [46M]
┃ ┃ ┣━━26.2MER—推广成本营收-.mp4 [16.9M]
┃ ┃ ┣━━26.3CAC—顾客获取成本及其他重要指标.mp4 [33.7M]
┃ ┃ ┣━━26.4STP框架.mp4 [21M]
┃ ┃ ┣━━26.5STP举例：地毯纤维.mp4 [14.5M]
┃ ┃ ┣━━26.6市场细分需要收集的数据.mp4 [38.6M]
┃ ┃ ┣━━26.7市场细分的主要步骤及聚类分析举例.mp4 [13.4M]
┃ ┃ ┣━━26.8Case Study：应当选择-个细分市场？.mp4 [28.6M]
┃ ┃ ┗━━26.9目标市场、市场定位及行业前瞻.mp4 [36.9M]
┃ ┣━━第 27 讲Best Practice in Data Processing [461.4M]
┃ ┃ ┣━━27.10Missing Data与Transformation.mp4 [29.6M]
┃ ┃ ┣━━27.11Web Data Preparation.mp4 [9.4M]
┃ ┃ ┣━━27.12Data Cleaning：Airbnb Listings（一）.mp4 [42.8M]
┃ ┃ ┣━━27.13Data Cleaning：Airbnb Listings（二）.mp4 [42.9M]
┃ ┃ ┣━━27.14Data Cleaning：Airbnb Listings（三）.mp4 [46.6M]
┃ ┃ ┣━━27.1数据处理方法引入.mp4 [23.5M]
┃ ┃ ┣━━27.2Data Source：Excel.mp4 [29.4M]
┃ ┃ ┣━━27.3Data Source：Delimited format与Fixed length.mp4 [46.7M]
┃ ┃ ┣━━27.4Data File与Web Data.mp4 [23.2M]
┃ ┃ ┣━━27.5Data Source：RDBMS.mp4 [44.5M]
┃ ┃ ┣━━27.6Data Types（一）.mp4 [36.5M]
┃ ┃ ┣━━27.7Data Types（二）.mp4 [22.3M]
┃ ┃ ┣━━27.8Missing Data与Data Quality Issues.mp4 [35.8M]
┃ ┃ ┗━━27.9Data Preparation与Data Cleansing.mp4 [28.2M]
┃ ┣━━第 28 讲Machine Learning [428.8M]
┃ ┃ ┣━━28.10Feature Extraction（一）.mp4 [20.6M]
┃ ┃ ┣━━28.11Feature Extraction（二）.mp4 [28.9M]
┃ ┃ ┣━━28.12答疑：Sklearn安装.mp4 [25.1M]
┃ ┃ ┣━━28.13Feature selection.mp4 [20M]
┃ ┃ ┣━━28.14Learning algorithm（一）.mp4 [24.5M]
┃ ┃ ┣━━28.15Learning algorithm（二）.mp4 [26.4M]
┃ ┃ ┣━━28.16Extreme Example.mp4 [29.9M]
┃ ┃ ┣━━28.17Model evaluation&selection及回顾.mp4 [27.8M]
┃ ┃ ┣━━28.1Sklearn介绍.mp4 [40.5M]
┃ ┃ ┣━━28.2什么是机器学习.mp4 [35.9M]
┃ ┃ ┣━━28.3General Learning Models-Supervised（一）.mp4 [30.8M]
┃ ┃ ┣━━28.4General Learning Models-Supervised（二）.mp4 [17.5M]
┃ ┃ ┣━━28.5General Learning Models-Unsupervised.mp4 [8.3M]
┃ ┃ ┣━━28.6Part1.Feature Extraction.mp4 [18M]
┃ ┃ ┣━━28.7Part2.Learning Algorithms.mp4 [17.2M]
┃ ┃ ┣━━28.8Sklearn安装.mp4 [13.6M]
┃ ┃ ┗━━28.9Dataset.mp4 [43.9M]
┃ ┣━━第 29 讲Linear Regression [403.4M]
┃ ┃ ┣━━29.10模型的诊断（二）.mp4 [22.7M]
┃ ┃ ┣━━29.11线性回归分析步骤.mp4 [16.6M]
┃ ┃ ┣━━29.12Python实例：利用数据点建立模型.mp4 [24.1M]
┃ ┃ ┣━━29.13如何求线性方程斜率与截距.mp4 [20.6M]
┃ ┃ ┣━━29.14如何评价模型的好坏.mp4 [11.9M]
┃ ┃ ┣━━29.15Linear Regression on Boston housing dataset.mp4 [38.1M]
┃ ┃ ┣━━29.16Method 1：sklearn package.mp4 [35M]
┃ ┃ ┣━━29.17Method 2：statsmodels package.mp4 [40.6M]
┃ ┃ ┣━━29.1课程引入.mp4 [15.4M]
┃ ┃ ┣━━29.2什么是模型？.mp4 [11M]
┃ ┃ ┣━━29.3什么是回归分析及其分类.mp4 [19.5M]
┃ ┃ ┣━━29.4什么是线性回归？.mp4 [21.4M]
┃ ┃ ┣━━29.5自变量与因变量.mp4 [15.7M]
┃ ┃ ┣━━29.6线性回归模型及所需满足的条件.mp4 [19.4M]
┃ ┃ ┣━━29.7线性回归前提假设.mp4 [38.6M]
┃ ┃ ┣━━29.8残差Residual及系数的估计.mp4 [23.6M]
┃ ┃ ┗━━29.9模型的诊断（一）.mp4 [29.3M]
┃ ┣━━第 3 讲Excel Basic（上） [827.7M]
┃ ┃ ┣━━3.10查找和替换（一）.mp4 [60.8M]
┃ ┃ ┣━━3.11查找和替换（二）.mp4 [68.5M]
┃ ┃ ┣━━3.12答疑.mp4 [53.1M]
┃ ┃ ┣━━3.1Excel简介.mp4 [97M]
┃ ┃ ┣━━3.2Excel基本操作（一）.mp4 [94M]
┃ ┃ ┣━━3.3Excel基本操作（二）.mp4 [54M]
┃ ┃ ┣━━3.4Excel基本操作（三）.mp4 [39.7M]
┃ ┃ ┣━━3.5行列及区域（一）.mp4 [69.7M]
┃ ┃ ┣━━3.6行列及区域（二）.mp4 [68M]
┃ ┃ ┣━━3.7数据及数据类型（一）.mp4 [69.4M]
┃ ┃ ┣━━3.8数据及数据类型（二）.mp4 [57.6M]
┃ ┃ ┗━━3.9数据及数据类型（三）.mp4 [95.8M]
┃ ┣━━第 30 讲Logistic Regression [375.4M]
┃ ┃ ┣━━30.10过拟合vs欠拟合与交叉验证.mp4 [36.7M]
┃ ┃ ┣━━30.11逻辑回归分析流程.mp4 [8.2M]
┃ ┃ ┣━━30.12数据导入.mp4 [26.9M]
┃ ┃ ┣━━30.13Data Exploratory.mp4 [34.7M]
┃ ┃ ┣━━30.14Create dummy variables & Feature Selection.mp4 [28.5M]
┃ ┃ ┣━━30.15Implementing the model & Logistic Regression Model Fitting.mp4 [16.4M]
┃ ┃ ┣━━30.16Cross Validation & Confusion Matrix.mp4 [26M]
┃ ┃ ┣━━30.1课程引入.mp4 [14.5M]
┃ ┃ ┣━━30.2监督式vs非监督式机器学习.mp4 [40.8M]
┃ ┃ ┣━━30.3分类vs聚类.mp4 [35.1M]
┃ ┃ ┣━━30.4分类算法vs回归分析.mp4 [6.3M]
┃ ┃ ┣━━30.5为什么线性模型不适用？.mp4 [17.4M]
┃ ┃ ┣━━30.6逻辑回归的前提假设.mp4 [17.9M]
┃ ┃ ┣━━30.7逻辑回归的公式及问题.mp4 [21.4M]
┃ ┃ ┣━━30.8混淆矩阵与ROC曲线.mp4 [34M]
┃ ┃ ┗━━30.9模型永远都不是完美的.mp4 [10.7M]
┃ ┣━━第 4 讲Excel Basic（下） [592.3M]
┃ ┃ ┣━━4.1答疑回顾.mp4 [62.1M]
┃ ┃ ┣━━4.2排序.mp4 [179.3M]
┃ ┃ ┣━━4.3排序插入.mp4 [38.3M]
┃ ┃ ┣━━4.4筛选（一）.mp4 [149M]
┃ ┃ ┣━━4.5筛选（二）.mp4 [95.8M]
┃ ┃ ┗━━4.6答疑.mp4 [67.7M]
┃ ┣━━第 5 讲Excel分类汇总、公式与函数 [787.4M]
┃ ┃ ┣━━5.10报名统计.mp4 [32.1M]
┃ ┃ ┣━━5.11SUMIF.mp4 [68.6M]
┃ ┃ ┣━━5.12SUMIF练习.mp4 [39M]
┃ ┃ ┣━━5.1分类汇总（一）.mp4 [187M]
┃ ┃ ┣━━5.2分类汇总（二）.mp4 [35.3M]
┃ ┃ ┣━━5.3公式与函数（一）.mp4 [47M]
┃ ┃ ┣━━5.4公式与函数（二）.mp4 [23.7M]
┃ ┃ ┣━━5.5公式与函数（三）.mp4 [63.6M]
┃ ┃ ┣━━5.6逻辑判断IF（一）.mp4 [71.3M]
┃ ┃ ┣━━5.7逻辑判断IF（二）.mp4 [76.4M]
┃ ┃ ┣━━5.8COUNTIF.mp4 [111.8M]
┃ ┃ ┗━━5.9重复.mp4 [31.6M]
┃ ┣━━第 6 讲Excel—VLOOKUP [512.3M]
┃ ┃ ┣━━6.1VLOOKUP.mp4 [46.4M]
┃ ┃ ┣━━6.2菜单、Join Two Tables.mp4 [25.5M]
┃ ┃ ┣━━6.3记录多匹配、跨表.mp4 [103.5M]
┃ ┃ ┣━━6.4跨表、跨文件薄.mp4 [74.1M]
┃ ┃ ┣━━6.5示例：王者荣耀、打标签.mp4 [29.8M]
┃ ┃ ┣━━6.6文本vlookup、Hlookup.mp4 [57.3M]
┃ ┃ ┣━━6.7Match&Index.mp4 [34.8M]
┃ ┃ ┣━━6.8返回多列.mp4 [53.8M]
┃ ┃ ┗━━6.9认识数组、记录多匹配.mp4 [87.2M]
┃ ┣━━第 7 讲商务智能 [436.9M]
┃ ┃ ┣━━7.1商务智能含义（一）.mp4 [15.5M]
┃ ┃ ┣━━7.2商务智能含义（二）.mp4 [46M]
┃ ┃ ┣━━7.3数据仓库系统.mp4 [58.7M]
┃ ┃ ┣━━7.4常见BI.mp4 [24.9M]
┃ ┃ ┣━━7.5Power BI（一）.mp4 [69.9M]
┃ ┃ ┣━━7.6Power BI（二）.mp4 [136.3M]
┃ ┃ ┗━━7.7答疑.mp4 [85.6M]
┃ ┣━━第 8 讲Python基础（上） [711.9M]
┃ ┃ ┣━━8.10Python for basic data type（一）.mp4 [61.4M]
┃ ┃ ┣━━8.11Python for basic data type（二）.mp4 [31.6M]
┃ ┃ ┣━━8.12Python for basic data type（三）.mp4 [43.1M]
┃ ┃ ┣━━8.13Python for basic data type（四）.mp4 [39.2M]
┃ ┃ ┣━━8.14Python for basic data type（五）.mp4 [38.6M]
┃ ┃ ┣━━8.15Python for basic data type（六）.mp4 [26.6M]
┃ ┃ ┣━━8.16Python for basic data type（七）.mp4 [28.5M]
┃ ┃ ┣━━8.17Python for basic data type（八）.mp4 [66.2M]
┃ ┃ ┣━━8.1Python基础课程.mp4 [18.7M]
┃ ┃ ┣━━8.2Python能做什么.mp4 [31.4M]
┃ ┃ ┣━━8.3Python20载.mp4 [78.6M]
┃ ┃ ┣━━8.4Python简单介绍.mp4 [38.3M]
┃ ┃ ┣━━8.5工具安装及环境配置（一）.mp4 [27.4M]
┃ ┃ ┣━━8.6工具安装及环境配置（二）.mp4 [31.4M]
┃ ┃ ┣━━8.7计算机与程序思维.mp4 [34M]
┃ ┃ ┣━━8.8Jupyter notebook（一）.mp4 [51.9M]
┃ ┃ ┗━━8.9Jupyter notebook（二）.mp4 [65.1M]
┃ ┗━━第 9 讲Python基础（中） [984M]
┃ ┣━━9.10王者荣耀case function（三）.mp4 [153.1M]
┃ ┣━━9.11Quiz—基本语法及变量.mp4 [44.2M]
┃ ┣━━9.12Way to Function（一）.mp4 [37.9M]
┃ ┣━━9.13Way to Function（二）.mp4 [65.4M]
┃ ┣━━9.14Quiz—Code Structure（一）.mp4 [20.9M]
┃ ┣━━9.15Quiz—Code Structure（二）.mp4 [49.7M]
┃ ┣━━9.16Python basic data structure（一）.mp4 [44.2M]
┃ ┣━━9.17Python basic data structure（二）.mp4 [33.5M]
┃ ┣━━9.18Python basic data structure（三）.mp4 [50.4M]
┃ ┣━━9.1答疑.mp4 [47.3M]
┃ ┣━━9.2Python for basic data type（一）.mp4 [70.1M]
┃ ┣━━9.3Python for basic data type（二）.mp4 [50.3M]
┃ ┣━━9.4Quiz—字符串.mp4 [27.9M]
┃ ┣━━9.5Python Code Structure.mp4 [51.5M]
┃ ┣━━9.6While Loop.mp4 [39.7M]
┃ ┣━━9.7For Loop.mp4 [39.2M]
┃ ┣━━9.8王者荣耀case function（一）.mp4 [97.1M]
┃ ┗━━9.9王者荣耀case function（二）.mp4 [61.6M]
┣━━课件 [1.2G]
┃ ┣━━1-3讲 商业数据分析综述及Excel Basic.zip [24M]
┃ ┣━━4-7讲 Excel Basic；分类汇总、函数与公式；Vlookup；商务智能.zip [46.5M]
┃ ┣━━8-11讲 Python基础上+中+下及进阶和面向对象.zip [10.6M]
┃ ┣━━12讲 网络数据获取.zip [10M]
┃ ┣━━13-15讲 概率论基本概念；随机变量及其分布（上+下）.zip [16.5M]
┃ ┣━━16-17讲 随机变量的数字特征；多维随机变量.zip [8.5M]
┃ ┣━━18讲 数理统计及SPSS应用.zip [190B]
┃ ┣━━19讲 Python Numpy，Pandas.zip [102.6K]
┃ ┣━━20讲 Matplotlib, Seaborn .zip [12.8M]
┃ ┣━━21讲 Excel数据透视表.zip [798.3K]
┃ ┣━━22讲 数据可视化.zip [1.2M]
┃ ┣━━23讲 数据仪表盘Excel Dashboard.zip [6.5M]
┃ ┣━━24讲 商业流程综述Business Process Overview.zip [6.2M]
┃ ┣━━25讲 Marketing Analytics.zip [63M]
┃ ┣━━26讲 市场推广分析Marketing Analytics.zip [7.3M]
┃ ┣━━27讲 Best practice in data processing.zip [14.7M]
┃ ┣━━0220.zip [2.8M]
┃ ┣━━0221.zip [3M]
┃ ┣━━0222.zip [3.6M]
┃ ┣━━0223-分类与聚类.zip [9.6M]
┃ ┣━━0224.zip [4.8M]
┃ ┣━━0225.zip [617K]
┃ ┣━━0226—SPSS与问卷数据分析.zip [2.7M]
┃ ┣━━0227—市场调查的基础知识V1.pdf [911.8K]
┃ ┣━━0301-CRM & RFM.zip [24.3M]
┃ ┣━━0302-CRM & RFM .zip [2.5M]
┃ ┣━━0303-BA I BD and Sales Chn.pdf [5.1M]
┃ ┣━━0304-GrowthHacking-V3.pdf [196.1M]
┃ ┣━━0305-MySQL 1.zip [17.6M]
┃ ┣━━0306-代码及数据.zip [37.5K]
┃ ┣━━0307-大数据与Power BI.zip [36M]
┃ ┣━━0309-E-Commerce-V4.pdf [27.8M]
┃ ┣━━0310-E-Commerce-2-V4.pdf [34.8M]
┃ ┣━━0312-Gaming Analytics.zip [14.7M]
┃ ┣━━0314-Gaming Analytics.zip [15.2M]
┃ ┣━━0316-感官分析.zip [277.6M]
┃ ┣━━0317-感官分析.zip [203.4M]
┃ ┣━━0319+0320-AB Testing.zip [20.6M]
┃ ┣━━0323-Capstone.zip [44.9M]
┃ ┗━━0324-Capstone.zip [29.7M]
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