About this Course
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Approx. 20 hours to complete

Suggested: 5 weeks of study, 1-2 hours/week...


Subtitles: English

Skills you will gain

Python ProgrammingApache HadoopMapreduceApache Spark

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Approx. 20 hours to complete

Suggested: 5 weeks of study, 1-2 hours/week...


Subtitles: English

Syllabus - What you will learn from this course

2 hours to complete

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. ...
7 videos (Total 53 min), 4 readings, 1 quiz
7 videos
The Apache Framework: Basic Modules3m
Hadoop Distributed File System (HDFS)5m
The Hadoop "Zoo"5m
Hadoop Ecosystem Major Components11m
Exploring the Cloudera VM: Hands-On Part 116m
Exploring the Cloudera VM: Hands-On Part 26m
4 readings
Apache Hadoop Ecosystem10m
Lesson 1 Slides (PDF)10m
Hardware & Software Requirements10m
Lesson 2 Slides - Cloudera VM Tour10m
1 practice exercise
Basic Hadoop Stack20m
3 hours to complete

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....
10 videos (Total 70 min), 6 readings, 3 quizzes
10 videos
The Hadoop Distributed File System (HDFS) and HDFS28m
MapReduce Framework and YARN8m
The Hadoop Execution Environment4m
YARN, Tez, and Spark11m
Hadoop Resource Scheduling6m
Hadoop-Based Applications3m
Introduction to Apache Pig7m
Introduction to Apache HIVE7m
Introduction to Apache HBASE7m
6 readings
Hadoop Basics - Lesson 1 Slides10m
Lesson 2: Hadoop Execution Environment - Slides10m
Lesson 3: Hadoop-Based Applications Overview - All Slides10m
Command list for Applications Slides10m
Tips to handle service connection errors10m
References for Applications10m
3 practice exercises
Overview of Hadoop Stack10m
Hadoop Execution Environment14m
Hadoop Applications12m
2 hours to complete

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....
9 videos (Total 58 min), 5 readings, 3 quizzes
9 videos
The HDFS Performance Envelope5m
Read/Write Processes in HDFS4m
HDFS Tuning Parameters6m
HDFS Performance and Robustness9m
Overview of HDFS Access, APIs, and Applications5m
HDFS Commands8m
Native Java API for HDFS4m
5 readings
Lesson 1: Introduction to HDFS - Slides10m
HDFS references10m
Lesson 2: HDFS Performance and Tuning - Slides10m
HDFS Access, APIs10m
Lesson 3: HDFS Access, APIs, Applications - Slides10m
3 practice exercises
HDFS Architecture12m
HDFS performance,tuning, and robustness10m
Accessing HDFS12m
7 hours to complete

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....
9 videos (Total 27 min), 3 readings, 3 quizzes
9 videos
The Map/Reduce Framework2m
A MapReduce Example: Wordcount in detail4m
MapReduce: Intro to Examples and Principles2m
MapReduce Example: Trending Wordcount1m
MapReduce Example: Joining Data4m
MapReduce Example: Vector Multiplication2m
Computational Costs of Vector Multiplication3m
MapReduce Summary2m
3 readings
Lesson 1: Introduction to MapReduce - Slides10m
A note on debugging map/reduce programs.10m
Lesson 2: MapReduce Examples and Principles - Slides10m
1 practice exercise
Lesson 1 Review14m
8 hours to complete


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. Spark provides great performance advantages over Hadoop MapReduce,especially for iterative algorithms, thanks to in-memory caching. Also, gives Data Scientists an easier way to write their analysis pipeline in Python and Scala,even providing interactive shells to play live with data....
10 videos (Total 70 min), 4 readings, 5 quizzes
10 videos
Architecture of Spark7m
Resilient Distributed Datasets10m
Spark Transformations10m
Wide Transformations10m
Directed Acyclic Graph (DAG) Scheduler8m
Actions in Spark2m
Memory Caching in Spark5m
Broadcast Variables2m
4 readings
Setup PySpark on the Cloudera VM10m
Lesson 1: Intro to Apache Spark - Slides10m
Lesson 2: RDD and Transformations - Slides10m
Lesson 3: Scheduling, Actions, Caching - Slides10m
3 practice exercises
Spark Lesson 112m
Spark Lesson 210m
Spark Lesson 312m
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Top Reviews

By GMFeb 1st 2016

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.

By GCOct 25th 2015

Super hands on introduction to key Hadoop components, such as Spark, Map Reduce, Hive, Pig, HBase, HDFS, YARN, Squoop and Flume.\n\nI can't wait to the next course on the specialization.



Natasha Balac

Director, Predictive Analytics Center of Excellence (PACE)
San Diego Supercomputer Center

Paul Rodriguez

Research Programmer
San Diego Supercomputer Center (SDSC)

Andrea Zonca

HPC Applications Specialist
San Diego Supercomputer Center (SDSC)

About University of California San Diego

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....

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