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
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Approx. 26 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, English, Spanish
Skills you will gain
- Python Programming
- Apache Hadoop
- Mapreduce
- Apache Spark
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Approx. 26 hours to complete
English
Subtitles: Arabic, French, Portuguese (European), Italian, Vietnamese, German, Russian, 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
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
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
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
Reviews
- 5 stars45.41%
- 4 stars28.05%
- 3 stars12.37%
- 2 stars6.71%
- 1 star7.44%
TOP REVIEWS FROM HADOOP PLATFORM AND APPLICATION FRAMEWORK
by MTOct 5, 2016
Covers the basics well, but lacks depth and integration between the weeks. E.g. it would be nice to see how to use Spark + HDFS together and what the efficiency considerations are.
by ABMay 14, 2017
Great course with great explanations. I just want to suggest to use more visual examples during your explanations, I mean, it would be nice to see live examples of code and executions running.
by WJOct 25, 2020
The presentation of some of the lecture materials was quite bad. It'd help if you already had some foundation. It did help me reinforce my understanding and I did learn something new.
by DAMay 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.
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