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所在平台: Udemy |
课程主页: https://www.udemy.com/course/data-science-project-management-methodology-crisp-dm/
课程评论：没有评论
《数据科学：项目管理方法论 - CRISP-DM - 2025》课程概述 本课程旨在提升数据相关项目的成功率，通过结构化的方法论，揭示数据如何助力组织做出明智的数据驱动决策。如同“新石油”般，数据驱动着各行各业的竞争优势。 课程内容涵盖： * **大数据分析应用：** 学习大数据分析的实时应用，并通过实际用例理解其必要性。 * **CRISP-DM 方法论：** 深入学习数据挖掘领域的最佳项目管理方法论 CRISP-DM，了解其从初级到高级的各项原理。 * **端到端项目管理：** 掌握 CRISP-DM 方法论在数据科学和人工智能项目中的完整生命周期管理，包括以下六个阶段： * **业务理解（Business Understanding）** * **数据理解（Data Understanding）** * **数据准备（Data Preparation）** * **数据建模（Data Modeling）** * **模型评估（Model Evaluation）** * **模型部署（Model Deployment）** * **数据处理技术：** 学习数据收集、数据清洗、数据准备、数据整理 (Data Munging)、数据封装 (Data Wrapping) 等关键技术。 * **探索性数据分析 (EDA)：** 掌握数据预处理的初步步骤，包括探索性数据分析，以揭示数据中的潜在信息。 * **统计学基础：** 学习用于从数据中提取信息的统计计算，特别是描述性分析。 * **概率分布：** 理解连续概率分布的原理，掌握连续随机变量的特性及其在正态条件下的分布。学习标准变量及其分布的特性，并利用正态 Q-Q 图检验连续随机变量是否服从正态分布。 * **统计估计：** 学习如何利用样本数据来估计总体数值的科学方法。 本课程将为学习者提供管理数据科学和人工智能项目的全面知识体系，并掌握强大的 CRISP-DM 方法论。
This course includes a structured approach of handling the data related projects for maximizing the success rate. Learn about insights on how data is assisting organizations to make informed data-driven decisions. Data is treated as the new oil for all the industries and sectors which keep organizations ahead in the competition. Learn the application of Big Data Analytics in real-time, you will understand the need for analytics with a use case. Also, learn about the best project management methodology for Data Mining - CRISP-DM at a high level.Learners will understand about Project management methodology - CRISP-DM, in handling Data Science projects or Artificial Intelligence projects end to end. Learn about all the 6 stages including Business Understanding, Data Understanding, Data Preparation, Data Modeling, Model Evaluation and finally Model Deployment. Learn about Data Collection, Data Cleansing, Data Preparation, Data Munging, Data Wrapping, etc. Learn about the preliminary steps taken to churn the data, known as exploratory data analysis. In this module, you also are introduced to statistical calculations which are used to derive information from data. We will begin to understand how to perform a descriptive analysis. Learn about continuous probability distribution. Understand the properties of a continuous random variable and its distribution under normal conditions. To identify the properties of a continuous random variable, statisticians have defined a variable as a standard, learning the properties of the standard variable and its distribution. You will learn to check if a continuous random variable is following normal distribution using a normal Q-Q plot. Learn the science behind the estimation of value for a population using sample data.
