Hadoop Developer

Learn to install, implement various components of Hadoop like Pig, Hive, Flume, Sqoop and YARN.

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Intermediate

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27 Hours

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Learn to install, implement various components of Hadoop like Pig, Hive, Flume, Sqoop and YARN.

Course Information

About this course:

This Hadoop Developer Training will help you get a detailed idea about Big Data and Hadoop. Some of the topics included are introduction to the Hadoop ecosystem, understanding of HDFS and MapReduce including MapReduce abstraction. Learn to install, implement various components of Hadoop like Pig, Hive, Flume, Sqoop and YARN.

The average salary for a Hadoop Developer is $119,250 per year.

Course Objective:

  • Learn the Hadoop Architecture and Hadoop basics for beginners
  • Learn what is Hadoop, HDFS and MapReduce framework
  • Write MapReduce programs and deploy Hadoop clusters
  • Develop applications for Big Data using Hadoop Technology
  • Develop YARN programs on the Hadoop 2.X version
  • Work on Big Data analytics using Hive, Pig and YARN
  • Integrate MapReduce and HBase to do advanced usage and Indexing
  • Learn fundamentals of Spark framework and its working
  • Understand RDD in Apache Spark
  • Learn Hadoop development best practices
  • Job scheduling using Oozie
  • Prepare for the Cloudera Spark and Hadoop Developer Certification

Audience:

  • Software Developers, analytics, BI, ETL, and data warehousing professionals
  • Big Data Hadoop developers, architects and testing personnel

Prerequisite:

  • You don’t need prior knowledge of Apache Hadoop.

Outline

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Subjects Big Data
Lab Access No
Technology Hadoop
Learning Style Self-Paced Learning
Learning Type Course
Difficulty Intermediate
Course Duration 27 Hours
Language English
VPA Discount VPA Discount

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Course Expert:

Author

Tom Robertson
(Data Science Enthusiast)

Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.

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