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所在平台: Udemy |
课程主页: https://www.udemy.com/course/taming-big-data-with-mapreduce-and-hadoop/
课程评论：没有评论
课程名称：掌控大数据：MapReduce 和 Hadoop 实操 课程概述：“大数据”分析是一项热门且极具价值的技能，本课程将快速教您两种大数据的基本技术：MapReduce 和 Hadoop。您是否曾好奇 Google 如何持续分析整个互联网？您将学习相同的技术，并在自己的 Windows 系统上进行实践。通过超过 10 个实践示例，学习并掌握将数据分析问题框架化为 MapReduce 问题的技巧，并将其扩展到云计算服务上。 本课程将由曾任亚马逊和 IMDb 的工程师和高级经理授课。您将学习以下内容： - MapReduce 的概念 - 使用 Python 和 MRJob 快速运行 MapReduce 任务 - 将复杂分析问题转化为多阶段的 MapReduce 任务 - 使用亚马逊的弹性 MapReduce 服务扩展到更大的数据集 - 理解 Hadoop 如何在计算集群中分配 MapReduce 任务 - 了解其他 Hadoop 技术，如 Hive、Pig 和 Spark 到本课程结束时，您将能够在云中运行分析数吉字节信息的代码，时间仅需几分钟。我们会在学习过程中享受乐趣，初步接触 MapReduce，使用电影评级数据和书本文本进行分析。掌握基础后，将转向更复杂和有趣的任务，例如使用一百万条电影评分数据找到相似的电影，或者分析超级英雄的社交图谱，识别出“最受欢迎”的超级英雄，并开发一个系统来查找超级英雄之间的“隔离程度”。 本课程内容非常实操，您将大部分时间跟随讲师的引导，编写、分析和运行真实代码，既包括在您自己的系统上运行，也包括使用亚马逊的弹性 MapReduce 服务。课程包含超过 5 小时的视频内容以及 10 个实际案例，复杂程度逐渐上升，您可以根据自己的节奏和时间安排进行学习。课程最后将介绍其他基于 Hadoop 的技术，包括 Hive、Pig，以及当前火热的 Spark 框架，并提供一个基于 Spark 的实例。 我们的学生给予了很高的评价：“我参加过许多 MapReduce 的课程，这无疑是最好的，远超其他课程。” “这是我在 Udemy 上使用的 4 年中看到的最佳课程。” “这是关于 MapReduce 和 Python 的最佳实操课程，我非常喜欢这个自己动手的学习方式，一切都组织得井井有条，讲师也是顶尖的。”
"Big data" analysis is a hot and highly valuable skill - and this course will teach you two technologies fundamental to big data quickly: MapReduce and Hadoop. Ever wonder how Google manages to analyze the entire Internet on a continual basis? You'll learn those same techniques, using your own Windows system right at home. Learn and master the art of framing data analysis problems as MapReduce problems through over 10 hands-on examples, and then scale them up to run on cloud computing services in this course. You'll be learning from an ex-engineer and senior manager from Amazon and IMDb. Learn the concepts of MapReduce Run MapReduce jobs quickly using Python and MRJob Translate complex analysis problems into multi-stage MapReduce jobs Scale up to larger data sets using Amazon's Elastic MapReduce service Understand how Hadoop distributes MapReduce across computing clusters Learn about other Hadoop technologies, like Hive, Pig, and Spark By the end of this course, you'll be running code that analyzes gigabytes worth of information - in the cloud - in a matter of minutes. We'll have some fun along the way. You'll get warmed up with some simple examples of using MapReduce to analyze movie ratings data and text in a book. Once you've got the basics under your belt, we'll move to some more complex and interesting tasks. We'll use a million movie ratings to find movies that are similar to each other, and you might even discover some new movies you might like in the process! We'll analyze a social graph of superheroes, and learn who the most "popular" superhero is - and develop a system to find "degrees of separation" between superheroes. Are all Marvel superheroes within a few degrees of being connected to The Incredible Hulk? You'll find the answer. This course is very hands-on; you'll spend most of your time following along with the instructor as we write, analyze, and run real code together - both on your own system, and in the cloud using Amazon's Elastic MapReduce service. Over 5 hours of video content is included, with over 10 real examples of increasing complexity you can build, run and study yourself. Move through them at your own pace, on your own schedule. The course wraps up with an overview of other Hadoop-based technologies, including Hive, Pig, and the very hot Spark framework - complete with a working example in Spark. Don't take my word for it - check out some of our unsolicited reviews from real students: "I have gone through many courses on map reduce; this is undoubtedly the best, way at the top." "This is one of the best courses I have ever seen since 4 years passed I am using Udemy for courses." "The best hands on course on MapReduce and Python. I really like the run it yourself approach in this course. Everything is well organized, and the lecturer is top notch."
