This course is for novice programmers or business people who'd like to understand the core tools used to wrangle and analyze big data. With no prior experience, you'll 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.

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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 processes.

Syllabus

Week 1

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.

Week 2

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.

Week 3

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.

Week 4

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.

Week 5

Spark

Welcome to module 5, Introduction to Spark, this week we will focus on the Apache Spark cluster computing framework, an important contender of Hadoop MapReduce in the Big Data Arena.