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.
Offered By
Hadoop Platform and Application Framework
University of California San DiegoAbout this Course
33,498 recent views
Learner Career Outcomes
29%
started a new career after completing these courses
28%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 26 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish
Skills you will gain
Python ProgrammingApache HadoopMapreduceApache Spark
Learner Career Outcomes
29%
started a new career after completing these courses
28%
got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Approx. 26 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Chinese (Simplified), Italian, Vietnamese, Korean, German, Russian, Turkish, English, Spanish
Offered by
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.
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.
2 hours to complete
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 Stack30m
4 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.
4 hours to complete
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 Stack30m
Hadoop Execution Environment30m
Hadoop Applications30m
3 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.
3 hours to complete
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
REST API for HDFS8m
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 Architecture30m
HDFS performance,tuning, and robustness30m
Accessing HDFS30m
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.
7 hours to complete
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 Review30m
Reviews
TOP REVIEWS FROM HADOOP PLATFORM AND APPLICATION FRAMEWORK
by CADec 9, 2015
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.
by GMJan 31, 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 NPMay 15, 2020
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.
by GCOct 24, 2015
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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I purchase the Certificate?
Is financial aid available?
More questions? Visit the Learner Help Center.
