Combo Program

★★★★★

(2,088 ratings) 50,000+ Student

CORE JAVA + BIGDATA COMBO Training in Pune

A Core Java and Big Data combo refers to the integration of programming skills in Java with expertise in handling and analyzing large-scale data sets, typically associated with big data technologies. the Core Java and Big Data combo equips individuals with the programming skills and tools needed to work with and extract insights from massive datasets.

Radical Technologies

50,000+ English 21 Modules · 3 Courses

Online / Classroom

CORE JAVA + BIGDATA COMBO

Introduction To Java + Introduction to functional style of programming + HADOOP DEV + SPARK & SCALA

Courses Included 3 Courses (Introduction To Java + Introduction to functional style of programming + HADOOP DEV + SPARK & SCALA)

Batch Type Weekdays / Weekends

Mode of Training Classroom / Online / Corporate

Locations Pune, Bangalore, Kochi

Language English

Certification Globally Recognized

Tools you'll master

Java SQL Big Data MongoDB Splunk Data Analysis Spring Boot Selenium Linux

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100% placement assistance

What you'll learn

What is Core Java?

COURSE CONTENT

Tools

IDE Tools

Why Hadoop?

COURSE CONTENT

Programme Overview

21 modules across Introduction To Java, Introduction to functional style of programming, HADOOP DEV + SPARK & SCALA — a single, progressive learning arc from foundational concepts to real-world projects.

Courses Combined

Total Modules

364

Total Topics

4.8★

Average Rating

50K+

Students Trained

Introduction To Java

Master the core concepts and hands-on skills of Introduction To Java — from fundamentals to real-world application.

Java Selenium

Introduction to functional style of programming

Master the core concepts and hands-on skills of Introduction to functional style of programming — from fundamentals to real-world application.

Java

HADOOP DEV + SPARK & SCALA

Master the core concepts and hands-on skills of HADOOP DEV + SPARK & SCALA — from fundamentals to real-world application.

SQL Big Data MongoDB

Who is this programme for?

Whether you're starting from scratch, know some SQL, or are already writing code — this programme takes you from database fundamentals through Python programming to real-world data analysis.

Students & Freshers

Build a strong foundation in CORE JAVA + BIGDATA COMBO and gain practical, job-ready experience from day one.

Working Professionals

Upskill and combine complementary skills from multiple courses in one structured programme.

Career Switchers

Move into a new technical role with a single, structured path covering everything you need.

IT Professionals

Deepen your expertise and broaden your skill set with hands-on, practical training.

Course Curriculum

3 courses • 21 modules • 364 topics

Introduction To Java

Courses Combined

100% Practical · Unlimited Doubt Sessions

It lays the foundation in terms of rich concepts and unique style of implementation

setting a benchmark in the industry.

Being an open-source

many technologies like Selenium

Hadoop

Sales Force and Data analytics have based their implementation on Java.• It is basically used to build stand-alone applications.

What is Java

Java Flavors

characteristics

JVM Architecture

Bytecode

Class Loader

Unicode

Classpath

Path

Obect Oriented concepts (OOP)

Keywords

Datatypes

Variables

Operators

Casting

Selection statement (if, switch)

Control statements (while, do while, for)

Conditional statements (if, else, elseif, ? ? )

Static

Arrays

Classes and Objects

Structure of a class – its internals (Data Members, methods)

Using static

Constructor

this keyword

modifiers

playing with the object (copying, casting)

Garbage collection

Abstract class

Basics (extends keyword)

Modifiers and their scope

Deriving a class

super

final keyword

why java does not support multiple inheritance?

overloading a method

overloading a constructor

method overriding

accessing base class method

basics

modifiers and their scope chart

setting classpath

compiling and accessing a packaged class

types of packages

user defined package

String

StringBuffer

Arrays

Wrapper classes

Basics

Hierarchy of exceptions

Handling exception – Try

catch

finally

throw

throws

User defined exceptions

Basics

Thread class

Runnable Interface

Thread model

Life cycle – start()

run()

Scheduling

Deadlocks/Concurrency issues

Synchronization – as a block

as a modifier

Daemon thread

Introduction

Hierarchy of streams

IO Stream

Byte Stream

Character Streams

BufferedInputStream

BufferedOutputStream

Reader and Writer class

BufferedReader

PrintWriter

Serialization

basics

hierarchy

legacy classes – Vector

Queue

Stack

Enumeration

Dictionary

Properties

List

ArrayList

LinkedList

Set

HashSet

TreeSet

Map

HashMap

TreeMap

Generics

Annotations

Boxing/Unboxing

Enums

Introduction to functional style of programming

Courses Combined

100% Practical · Unlimited Doubt Sessions

Mini application – discussion/implementation

Javadoc

Javap

Jar

Eclipse

Myeclipse

Industry experienced Professional

Interview based Questions

Hands-On Practice

› Hands-on experience with Project orientation

Proper Communication with the student

Course Ends With One Live Project

Test on Each Topics

Certification Overview

Interview and resume preparation

Discussion on Real Time Scenarios

HADOOP DEV + SPARK & SCALA

Courses Combined

100% Practical · Unlimited Doubt Sessions

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.

HADOOP DEV + SPARK & SCALA + NoSQL + Splunk + HDFS (Storage) + YARN (Hadoop Processing Framework) + MapReduce using Java (Processing Data) + Apache Hive + Apache Pig + HBASE (Real NoSQL ) + Sqoop + Flume + Oozie + Kafka With ZooKeeper + Cassandra + MongoDB + Apache Splunk

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

Hadoop :

Why we need Hadoop

Data centers 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

Node Manager etc.

Job assignment & Execution flow

MapReduce using Java (Processing Data) :

The introduction of MapReduce.

MapReduce Architecture

Data flow in MapReduce

Understand Difference Between Block and InputSplit

Role of RecordReader

Basic Configuration of MapReduce

MapReduce life cycle

How MapReduce Works

Writing and Executing the Basic MapReduce Program using Java

Submission & Initialization of MapReduce Job.

File Input/Output Formats in MapReduce Jobs

Text Input Format

Key Value Input Format

Sequence File Input Format

NLine Input Format

Joins

Map-side Joins

Reducer-side Joins

Word Count Example(or) Election Vote Count

Will cover five to Ten Map Reduce Examples with real time data

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

Hands on Multiple Real Time datasets

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

Hands On Two more examples daily use case data analysis in google. And Analysis on Date time dataset

HBASE (Real NoSQL) :

Introduction to HBASE

Basic Configurations of HBASE

Fundamentals of HBase

What is NoSQL?

HBase Data Model

Table and Row.

Column Family and Column Qualifier.

Cell and its Versioning

Categories of NoSQL Data Bases

Key-Value Database

Document Database

Column Family Database

HBASE Architecture

HMaster

Region Servers

Regions

MemStore

Store

SQL vs. NOSQL

How HBASE is differed from RDBMS

HDFS vs. HBase

Client-side buffering or bulk uploads

HBase Designing Tables

HBase Operations

Get

Scan

Put

Delete

Live Dataset

Sqoop :

Sqoop commands

Sqoop practical implementation

Importing data to HDFS

Importing data to Hive

Exporting data to RDBMS

Sqoop connectors

Flume :

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 :

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 :

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 :

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

Kafka With ZooKeeper :

What is Kafka

Cluster architecture With Hands On

Basic operation

Integration with spark

Integration with Camel

Additional Configuration

Security and Authentication

Apache Kafka With Spring Boot Integration

Running

Usecase

Apache Splunk :

Introduction & Installing Splunk

Play with Data and Feed the Data

Searching & Reporting

Visualizing Your Data

Advanced Splunk Concepts

Cassandra + MongoDB :

Introduction of NoSQL

What is NOSQL & N0-SQL Data Types

System Setup Process

MongoDB Introduction

MongoDB Installation

DataBase Creation in MongoDB

ACID and CAP Theorum

What is JSON and what all are JSON Features?

JSON and XML Difference

CRUD Operations – Create

Read

Update

Delete

Cassandra Introduction

Cassandra – Different Data Supports

Cassandra – Architecture in Detail

Cassandra’s SPOF & Replication Factor

Cassandra – Installation & Different Data Types

Database Creation in Cassandra

Tables Creation in Cassandra

Cassandra Database and Table Schema and Data

Update

Delete

Insert Data in Cassandra Table

Insert Data From File in Cassandra Table

Add & Delete Columns in Cassandra Table

Cassandra Collections

Tools & Technologies

Every tool and library listed here is installed, configured and used in a hands-on lab session.

Introduction To Java

Java

Covered in Introduction To Java

Selenium

Covered in Introduction To Java

Introduction to functional style of programming

Java

Covered in Introduction to functional style of programming

HADOOP DEV + SPARK & SCALA

SQL

Covered in HADOOP DEV + SPARK & SCALA

Big Data

Covered in HADOOP DEV + SPARK & SCALA

MongoDB

Covered in HADOOP DEV + SPARK & SCALA

Splunk

Covered in HADOOP DEV + SPARK & SCALA

Tools & Libraries

364+

Hands-On Topics

Total Modules

Courses Combined

You don't just learn CORE JAVA + BIGDATA COMBO. You apply it.

A combined capstone project across all 3 courses — the same way you'd apply these skills on the job.

PROJECT // 01

CORE JAVA + BIGDATA COMBO Capstone Project

→Introduction To Java

→Introduction to functional style of programming

→HADOOP DEV + SPARK & SCALA

Capstone Project Combined

Apply everything you learn across Introduction To Java, Introduction to functional style of programming, HADOOP DEV + SPARK & SCALA to one real-world project

Bring together every course in this programme into a single, end-to-end project — the same way you would apply these combined skills on the job.

A working project combining all course modules

Added directly to your project portfolio

Reviewed by mentors before you graduate

Stack Java SQL Big Data MongoDB Splunk Data Analysis Spring Boot Selenium Linux

Hands-on Practice Areas

Hands-on Practice: Introduction To Java Hands-on Practice: Introduction to functional style of programming Hands-on Practice: HADOOP DEV + SPARK & SCALA

All projects go directly into your portfolio & resume — reviewed by mentors before you graduate.

See Sample Project Reports

Upcoming Batches

No upcoming batches scheduled right now. Enquire to get notified.

Why Radical Technologies

Live Online Training

Highly practical oriented training
Installation support on your system
24/7 Email and Phone support
100% Placement Assistance
Global Certification Preparation
Trainer-Student Interactive Portal
Assignments and Projects by Mentors

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Live Classroom Training

Weekend / Weekdays / Morning / Evening batches
80:20 Practical and Theory ratio
Real-life Case Studies
Easy make-up for missed sessions
PSI | Kryterion | Redhat Test Centers
Lifetime Video Classroom Access (coming soon)
Resume Prep and Mock Interviews

Enroll Now

Self-Paced Training

Learn 300+ courses at your own time
50,000+ Satisfied Learners
Course Completion Certificate
Practical Labs available
Mentor Support available
Doubt Clearing Session available
10% Discounted Global Certification

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Global Certification

Radical Technologies is the leading IT certification institute in Pune, offering globally recognized certifications across various domains. With expert trainers and comprehensive materials, we ensure students gain in-depth knowledge and hands-on experience to excel in their careers. Our certification programs are tailored to meet industry standards — from cloud technologies to data science — empowering individuals to stay ahead in the ever-evolving tech landscape.

Career Services

At Radical Technologies, we are committed to your success beyond the classroom. Our 100% Job Assistance program ensures that you are not only equipped with industry-relevant skills but also guided through the job placement process. With personalised resume building, interview preparation, and access to our extensive network of hiring partners, we help you take the next step confidently into your IT career.