Radical Technologies
Aundh:+91 8055223360 | Kharadi: +91 8448448706


  • Solution for BigData Problem
  • Open Source Technology
  • Based on open source platforms
  • Contains several tool for entire ETL data processing Framework
  • It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools.
Satisfied Learners
One time class room registraion to click here Fee 1000/-

Clasroom training batch schedules:

Location Day/Duration Date Time Type
Aundh Weekday 19/03/2018 08:30 AM New Batch Quick Enquiry
Aundh Weekend 24/03/2018 11:00 AM New Batch Quick Enquiry
Aundh Weekend 24/03/2018 11:00 AM New Batch Quick Enquiry

Event batch schedules:

Location Day/Duration Start Date ₹ Price Book Seat
Pune 2 days 31/03/2018 ₹ 12000.00 Enroll Now

Online training batch schedules:

Mode Day/Duration Start Date End Date ₹ Price Book Seat
Online 8 Weeks, 3 Days 01/01/2018 28/02/2018 ₹ 16000.00 Enroll Now

Hadoop Developer / Analyst / SPARK + SCALA / Hadoop (Java + Non- Java) Track

Best Bigdata Hadoop Training with 2 Real-time Projects with 1 TB Data set

Duration of the Training : 8 to 10 weekends 

Bigdata Hadoop Syllabus

For whom Hadoop is?

IT folks who want to change their profile in a most demanding technology which is in demand by almost all clients in all domains because of below mentioned reasons-

  •  Hadoop is open source (Cost saving / Cheaper)
  •  Hadoop solves Big Data problem which is very difficult or impossible to solve using highly paid tools in market
  •  It can process Distributed data and no need to store entire data in centralized storage as it is there with other tools.
  •  Now a days there is job cut in market in so many existing tools and technologies because clients are moving towards a cheaper and efficient solution in market named HADOOP
  •  There will be almost 4.4 million jobs in market on Hadoop by next year.

Please refer below mentioned links:


Can I Learn Hadoop If I Don’t know Java?


It is a big myth that if a guy don’t know Java then he can’t learn Hadoop. The truth is that Only Map Reduce framework needs Java except Map Reduce all other components are based on different terms like Hive is similar to SQL, HBase is similar to RDBMS and Pig is script based.

Only MR requires Java but there are so many organizations who started hiring on specific skill set also like HBASE developer or Pig and Hive specific requirements. Knowing MapReuce also is just like become all-rounder in Hadoop for any requirement.

Why Hadoop?

  • Solution for BigData Problem
  • Open Source Technology
  • Based on open source platforms
  • Contains several tool for entire ETL data processing Framework
  • It can process Distributed data and no need to store entire data in centralized storage as it is required for SQL based tools. 


Training Syllabus                                                   ,

 Big data

  • Distributed computing
  • Data management – Industry Challenges
  • Overview of Big Data
  • Characteristics of Big Data
  • Types of data
  • Sources of Big Data
  • Big Data examples
  • What is streaming data?
  • Batch vs Streaming data processing
  • Overview of Analytics
  • Big data Hadoop opportunities


  • Why we need Hadoop
  • Data centres and Hadoop Cluster overview
  • Overview of Hadoop Daemons
  • Hadoop Cluster and Racks
  • Learning Linux required for Hadoop
  • Hadoop ecosystem tools overview
  • Understanding the Hadoop configurations and Installation.

HDFS (Storage)

  • HDFS
  • HDFS Daemons – Namenode, Datanode, Secondary Namenode
  • Hadoop FS and Processing Environment’s UIs
  • Fault Tolerant
    • High Availability
    • Block Replication
  • How to read and write files
  • Hadoop FS shell commands


YARN (Hadoop Processing Framework)

  • YARN
  • YARN Daemons – Resource Manager, NodeManager etc.
  • Job assignment & Execution flow

 Apache Hive

  • Data warehouse basics
  • OLTP vs OLAP Concepts
  • Hive
  • Hive Architecture
  • Metastore DB and Metastore Service
  • Hive Query Language (HQL)
  • Managed and External Tables
  • Partitioning & Bucketing
  • Query Optimization
  • Hiveserver2 (Thrift server)
  • JDBC , ODBC connection to Hive
  • Hive Transactions
  • Hive UDFs
  • Working with Avro Schema and AVRO file format

Apache Pig

  • Apache Pig
  • Advantage of Pig over MapReduce
  • Pig Latin (Scripting language for Pig)
  • Schema and Schema-less data in Pig
  • Structured , Semi-Structure data processing in Pig
  • Pig UDFs
  • HCatalog
  • Pig vs Hive Use case


  • Sqoop commands
  • Sqoop practical implementation
    • Importing data to HDFS
    • Importing data to Hive
    • Exporting data to RDBMS
  • Sqoop connectors


  • Flume commands
  • Configuration of Source, Channel and Sink
  • Fan-out flume agents
  • How to load data in Hadoop that is coming from web server or other storage
  • How to load streaming data from Twitter data in HDFS using Hadoop


  • Oozie
  • Action Node and Control Flow node
  • Designing workflow jobs
  • How to schedule jobs using Oozie
  • How to schedule jobs which are time based
  • Oozie Conf file


  • Scala
    • Syntax formation, Datatypes , Variables
  • Classes and Objects
  • Basic Types and Operations
  • Functional Objects
  • Built-in Control Structures
  • Functions and Closures
  • Composition and Inheritance
  • Scala’s Hierarchy
  • Traits
  • Packages and Imports
  • Working with Lists, Collections
  • Abstract Members
  • Implicit Conversions and Parameters
  • For Expressions Revisited
  • The Scala Collections API
  • Extractors
  • Modular Programming Using Objects


  • Spark
  • Architecture and Spark APIs
  • Spark components
    • Spark master
    • Driver
    • Executor
    • Worker
    • Significance of Spark context
  • Concept of Resilient distributed datasets (RDDs)
  • Properties of RDD
  • Creating RDDs
  • Transformations in RDD
  • Actions in RDD
  • Saving data through RDD
  • Key-value pair RDD
  • Invoking Spark shell
  • Loading a file in shell
  • Performing some basic operations on files in Spark shell
  • Spark application overview
  • Job scheduling process
  • DAG scheduler
  • RDD graph and lineage
  • Life cycle of spark application
  • How to choose between the different persistence levels for caching RDDs
  • Submit in cluster mode
  • Web UI – application monitoring
  • Important spark configuration properties
  • Spark SQL overview
  • Spark SQL demo
  • SchemaRDD and data frames
  • Joining, Filtering and Sorting Dataset
  • Spark SQL example program demo and code walk through

Introduction to Kafka (Optional*)

  • What is Kafka
  • Cluster architecture
  • Basic operation
  • Integration with spark
  • Usecase

Key Features

  • This training program contains multiple POCs /exercises/ assignments on each topics and two real time projects with problem statements and data sets
  • This training will be conducted in workshop mode with full hands-on in class
Review Date
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I completed my Hadoop in Radical.My Trainers teaching is probably the best training one could get for sure. You don't only get to learn but you also get the Experience level training here.
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Available certifications under Cloudera and Hortonworks

Depends upon the students requirements and the topics covered in the curriculam , we can prepare the candidates for the exam

Cloudera Certified Associate (CCA)

CCA Spark and Hadoop Developer

CCA Data Analyst

CCA Administrator

Cloudera Certified Professional (CCP)

CCP Data Engineer



for Hadoop developers using frameworks like Pig, Hive, Sqoop and Flume.



for developers responsible for developing Spark Core and Spark SQL applications in Scala or Python.



for developers who design, develop and architect Hadoop-based solutions written in the Java programming language.



Hortonworks certification for administrators who deploy and manage Hadoop clusters.



for an entry point and fundamental skills required to progress to the higher levels of the Hortonworks big data certification program.

Hadoop Certifications : Radical is accredited with Pearson Vue and Kriterion etc. We do conduct Exams in every  month and we have 100% Passing record for all the students who completed course form Radical technologies .Most demanding Hadoop Exams are Hortonworks  and Cloudera certifications .

Exam Preparation : After the course we provide for all our candidates free exam preparation session , which will guide them to pass the Respective modules of Hadoop exams.

Trainer is having 17 year experience in IT with 10 years in data warehousing &ETL experience. It has been six years now that he has been working extensively in BigData ecosystem toolsets for few of the banking-retail-manufacturing clients. He is a certified HDP-Spark Developer and Cloudera certified Hbase specialist. He also have done corporate sessions and seminars both in India and abroadRecently he was engaged by Pune University for 40 hour sessions on BigData analytics to the senior professors of Pune.

All faculties at our organization are currently working on the technologies in reputed organization. The curriculum that is imparted is not just some theory or talk with some PPTs. We absolutely frame the forum in such a way so that at the end the lessons are imparted in easy language and the contents are well absorbed by the candidates. The sessions are backed by hands-on assignment. Also that the faculties are industry experience so during the course he does showcase his practical stories.

  • How we are Different from Others : Covers each topics with Real Time Examples . Covers 8 Real time project and more than 72+ Assignments which is divided into Basic , Intermediate and  Advanced . Trainer from Real Time Industry with 9 years experience in DWH. Working as BI and Hadoop consultant having 3+ years in Bigdata & Hadoop real time implementation and migrations.
    This is completely hands own training , which covers 90% Practical And 10% Theory .Here in Radical Technologies , we will take all prerequisite like Java ,SQL, which is required to learn Hadoop Developer and Analytical skills. This way We will accommodate technology illiterate and Technical experts in the same session and at the end of the training , they will gain the confidence  that , they got up-skilled to a different level. 
    • 8 Domain Based Project With Real Time Data ( with one trainer – two project. If you req more projects , you are free to attend any other trainers project orientations sessions )
    • 5 POC
    • 72 Assignments
    • 25 Real Time Scenarios On 16 Node Clusters ( Aws Cloud setup )
    • Basic Java
    • DWH Concept
    • Pig|Hive|Mapreduce|Nosql|Hbase|Zookeeper|Sqoop|Flume|Oozie|Yarn|Hue|Spark |Scala

    42 Hours Classroom Section

    30 Hours of assignments

    25 hours for One Project and 50 Hrs for 2 Project ( Candidates should prepare with mentor support . 50 hours mentioned is total hours spent on project by each trainer )

    350+ Interview Questions

    Administration and Manual Installation of Hadoop with other Domain based projects will be done on regular basis apart from our normal batch schedule .

    We do have projects from Healthcare , Financial , Automotive ,Insurance , Banking , Retail etc , which will be given to our students as per their requirements .

    • Training By 14+ Years experienced Real Time Trainer
    • A pool of 200+ real time Practical Sessions on Bigdata Hadoop
    • Scenarios and Assignments to make sure you compete with current Industry standards
    • World class training methods
    • Training  until the candidate get placed
    • Certification and Placement Support until you get certified and placed
    • All training in reasonable cost
    • 10000+ Satisfied candidates
    • 5000+ Placement Records
    • Corporate and Online Training in reasonable Cost
    • Complete End-to-End Project with Each Course
    • World Class Lab Facility which facilitates I3 /I5 /I7 Servers and Cisco UCS Servers
    •  Covers Topics other than from Books which is required for the IT Industry
    • Resume And Interview preparation with 100% Hands-on Practical sessions
    • Doubt clearing sessions any time after the course
    • Happy to help you any time after the course

ML and GraphX ,’R’ Language

Data Analytics / Science

Cloudera Certified Professional (CCP)

CCP Data Engineer

Our Courses

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