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
Skills you will gain
- Python Programming
- Apache Hadoop
- Mapreduce
- Apache Spark
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
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.
Reviews
- 5 stars45.44%
- 4 stars28.03%
- 3 stars12.36%
- 2 stars6.71%
- 1 star7.44%
TOP REVIEWS FROM HADOOP PLATFORM AND APPLICATION FRAMEWORK
Easy into into big data architecture with minimal previous development requirements. Relevant to anyone who wants to grasp basic concepts of how data flows/processed/analyzed in hadoop.
Very good overview, but not extremely in-depth. It's a great course to get an understanding of the concepts and you can investigate deeper later into the topics that interest you.
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.
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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