HadoopTraining Courses

HadoopTraining Schedule

Training Course Dates Location

Big data is among the hottest trends in IT right now, and Hadoop stands front and center in the discussion of how to implement a big data strategy.

The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-availability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-available service on top of a cluster of computers, each of which may be prone to failures.

The project includes these modules:

  • Hadoop Common: The common utilities that support the other Hadoop modules.
  • Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
  • Hadoop YARN: A framework for job scheduling and cluster resource management.
  • Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.


Apache Spark advanced training is available for onsite training.

HadoopTraining Courses

Hadoop Novice to Professional Training Course

Hadoop Novice to Professional Training Course

Our Goal is your success:

You will enroll Vulab's Hadoop Novice to Professional training course excited and ready to work hard. Four weeks later, you will launch from our launch pad as a hero with lots of energy, knowledge and experience in Hadoop. You will be amazed at the portfolio that you have built during 28 days you slogged to become an expert in Hadoop. We challenge that you will be as competent or more competent than most of the developers even having 5 years of hadoop experience in the industry.

World Leading results:

Hadoop is the technology for managing data at small, medium and large corporations. You will master the techniques of deploying and creating solutions using Hadoop. 100% of Vulab Hadoop alumni are now software engineers with an average six figure starting salary and some of the developers even making half million USD per year. They work at large companies that turn away college graduates every day like Bank Of America, Ebay, Amazon, Merck, FaceBook, Groupon, Twitter. Our Hadoop programming use Vulab's industry leading big data solutions which is a first in the industry for faster products and first to market.

Building the world's best hadoop coding academy:

Our coding boot camp's rigorous application procedure, combined with a 100:1 application ratio means you will work with extremely driven and talented peers. Students complete real world projects during training. Your instructor Sri is having 25 years of industry experience and he is the best developer of Hadoop, You are learning from experienced developer and a professional to use the best training methods and tools. Our hadoop training course is scientifically engineered to maintain optimal pace with best curriculum and exercises. We also provide additional advanced learning materials to continue your learning process even after the course. You will have life long access to your instructor and forums after the class too.

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Hadoop Administrator Novice to Professional Training Course

  • The internals of YARN, MapReduce, and HDFS
  • Determining the correct hardware and infrastructure for your cluster
  • Proper cluster configuration and deployment to integrate with the data center
  • How to load data into the cluster from dynamically-generated files using Flume and from RDBMS using Sqoop
  • Configuring the FairScheduler to provide service-level agreements for multiple users of a cluster
  • Best practices for preparing and maintaining Apache Hadoop in production
  • Troubleshooting, diagnosing, tuning, and solving Hadoop issues
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Apache Spark Novice to Professional Training Course

After taking this class you will be able to:

  • Describe Spark’s fundamental mechanics
  • Use the core Spark APIs to operate on data
  • Articulate and implement typical use cases for Spark
  • Build data pipelines with SparkSQL and DataFrames
  • Analyze Spark jobs using the UIs and logs
  • Create Streaming and Machine Learning jobs
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