Introduction to Big Data

开始时间: 02/22/2020 持续时间: Unknown

所在平台: Coursera

课程类别: 计算机科学

大学或机构: CourseraNew

   

课程主页: https://www.coursera.org/learn/big-data-introduction

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Interested in increasing your knowledge of the Big Data landscape? This course is for those new to data science and interested in understanding why the Big Data Era has come to be. It is for those who want to become conversant with the terminology and the core concepts behind big data problems, applications, and systems. It is for those who want to start thinking about how Big Data might be useful in their business or career. It provides an introduction to one of the most common frameworks, Hadoop, that has made big data analysis easier and more accessible -- increasing the potential for data to transform our world! At the end of this course, you will be able to: * Describe the Big Data landscape including examples of real world big data problems including the three key sources of Big Data: people, organizations, and sensors. * Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and why each impacts data collection, monitoring, storage, analysis and reporting. * Get value out of Big Data by using a 5-step process to structure your analysis. * Identify what are and what are not big data problems and be able to recast big data problems as data science questions. * Provide an explanation of the architectural components and programming models used for scalable big data analysis. * Summarize the features and value of core Hadoop stack components including the YARN resource and job management system, the HDFS file system and the MapReduce programming model. * Install and run a program using Hadoop! This course is for those new to data science. No prior programming experience is needed, although the ability to install applications and utilize a virtual machine is necessary to complete the hands-on assignments. Hardware Requirements: (A) Quad Core Processor (VT-x or AMD-V support recommended), 64-bit; (B) 8 GB RAM; (C) 20 GB disk free. How to find your hardware information: (Windows): Open System by clicking the Start button, right-clicking Computer, and then clicking Properties; (Mac): Open Overview by clicking on the Apple menu and clicking “About This Mac.” Most computers with 8 GB RAM purchased in the last 3 years will meet the minimum requirements.You will need a high speed internet connection because you will be downloading files up to 4 Gb in size. Software Requirements: This course relies on several open-source software tools, including Apache Hadoop. All required software can be downloaded and installed free of charge. Software requirements include: Windows 7+, Mac OS X 10.10+, Ubuntu 14.04+ or CentOS 6+ VirtualBox 5+.

大数据入门:对增加您对大数据格局的了解感兴趣吗?本课程适用于数据科学新手,并且有兴趣了解为什么会出现大数据时代。它适用于那些希望熟悉大数据问题,应用程序和系统背后的术语和核心概念的人。它适合那些想开始考虑大数据在其业务或职业中可能有用的人。它介绍了最常见的框架之一Hadoop,该框架使大数据分析更容易且更易于访问-从而增加了数据改变我们世界的潜力! 在本课程结束时,您将能够: *描述大数据领域,包括现实世界中大数据问题的示例,包括大数据的三个关键来源:人员,组织和传感器。 *解释V的大数据(容量,速度,种类,准确性,价位和价值)以及为何每个因素都会影响数据收集,监视,存储,分析和报告。 *通过五步流程来构建分析,从大数据中获取价值。 *确定什么是大数据问题,什么不是大数据问题,并能够将大数据问题重铸为数据科学问题。 *提供用于可伸缩大数据分析的体系结构组件和编程模型的说明。 *总结了Hadoop核心堆栈组件的功能和价值,包括YARN资源和作业管理系统,HDFS文件系统以及MapReduce编程模型。 *使用Hadoop安装并运行程序! 本课程适用于数据科学新手。尽管需要具备安装应用程序和使用虚拟机的能力来完成动手分配,但不需要任何先验编程经验。 硬件要求: (A)四核处理器(建议支持VT-x或AMD-V),64位; (B)8 GB RAM; (C)20 GB可用磁盘。如何查找您的硬件信息:(Windows):通过单击“开始”按钮,右键单击“计算机”,然后单击“属性”,打开“系统”。 (Mac):通过单击Apple菜单,然后单击“关于本机”,打开“概述”。在过去3年中购买的大多数具有8 GB RAM的计算机都将满足最低要求。您将需要高速Internet连接。下载最大4 Gb的文件。 软件要求: 本课程依赖于几种开源软件工具,包括Apache Hadoop。可以免费下载和安装所有必需的软件。软件要求包括:Windows 7 +,Mac OS X 10.10 +,Ubuntu 14.04+或CentOS 6+ VirtualBox 5+。

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课程简介

Interested in increasing your knowledge of the Big Data landscape? This course is for those new to

课程标签

大数据 大数据介绍 大数据课程 大数据公开课 加州大学圣地亚哥分校 大数据专项课程

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