This course is for novice programmers or business people who would like to understand the core tools used to wrangle and analyze big data. With no prior experience, you will have the opportunity to walk through hands-on examples with Hadoop and Spark frameworks, two of the most common in the industry. You will be comfortable explaining the specific components and basic processes of the Hadoop architecture, software stack, and execution environment. In the assignments you will be guided in how data scientists apply the important concepts and techniques such as Map-Reduce that are used to solve fundamental problems in big data. You'll feel empowered to have conversations about big data and the data analysis process.
Об этом курсе
Карьерные результаты учащихся
29%
28%
Приобретаемые навыки
Карьерные результаты учащихся
29%
28%
от партнера

Калифорнийский университет в Сан-Диего
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Программа курса: что вы изучите
Hadoop Basics
Welcome to the first module of the Big Data Platform course. This first module will provide insight into Big Data Hype, its technologies opportunities and challenges. We will take a deeper look into the Hadoop stack and tool and technologies associated with Big Data solutions.
Introduction to the Hadoop Stack
In this module we will take a detailed look at the Hadoop stack ranging from the basic HDFS components, to application execution frameworks, and languages, services.
Introduction to Hadoop Distributed File System (HDFS)
In this module we will take a detailed look at the Hadoop Distributed File System (HDFS). We will cover the main design goals of HDFS, understand the read/write process to HDFS, the main configuration parameters that can be tuned to control HDFS performance and robustness, and get an overview of the different ways you can access data on HDFS.
Introduction to Map/Reduce
This module will introduce Map/Reduce concepts and practice. You will learn about the big idea of Map/Reduce and you will learn how to design, implement, and execute tasks in the map/reduce framework. You will also learn the trade-offs in map/reduce and how that motivates other tools.
Рецензии
Лучшие отзывы о курсе HADOOP PLATFORM AND APPLICATION FRAMEWORK
Very detailed , thorough introduction to a lot of the Hadoop ecosystem. Nice explanation and assignment to get a feel for Spark. At times a bit dry but altogether a well structured and taught course.
I'm forced to give 5 stars. I don't want to have a certification on a poor quality course (another coursera mistake). This material needs tremendous amount of work to get finished and revised.
Learned about Hadoop Ecosystem, limitations of map-reduce approach and Spark as a solution to overcome some of limitations.Thanks for giving me the opportunity to participate in this MOOC.
Super hands on introduction to key Hadoop components, such as Spark, Map Reduce, Hive, Pig, HBase, HDFS, YARN, Squoop and Flume. I can't wait to the next course on the specialization.
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Когда я получу доступ к лекциям и заданиям?
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Is financial aid available?
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