Big Data & Hadoop Certified Course in Jalandhar | Big Data Training in Jalandhar

Itronix Solutions provides Best Big Data & Hadoop Training in Jalandhar as per the current industry standards. Itronix Solutions is one of the most recommended Best Big Data & Hadoop Training Institute in Jalandhar that offers hands-on practical knowledge/ practical implementation on live case studies and will ensure the job with the help of advanced level Best Big Data & Hadoop Training Courses. At Itronix Solutions Best Big Data & Hadoop Training in Jalandhar is conducted by specialist working certified corporate professionals having 10+ years of experience in implementing real-time Best Big Data & Hadoop projects and case studies.

Big Data Traning Mohali

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Big Data and Hadoop Course Curriculum

Module 1: Introduction to Big Data

  • Introduction to Big Data and Hadoop
  • Big Data Analytics
  • What is Big Data?
  • Four v’s of Big Data
  • Rise of Big Data
  • Compare Hadoop vs traditional systems
  • Hadoop Master-Slave Architecture
  • Understanding HDFS Architecture
  • NameNode, DataNode, Secondary Node
  • Learn about JobTracker, TaskTracker, Resource Manager, Node Manager

Module 2: HDFS and MapReduce Architecture

  • Hadoop Architecture Distributed Storage (HDFS) and Yarn
  • What is HDFS
  • Need for HDFS
  • Regular File System vs HDFS
  • Characteristics of HDFS
  • HDFS Architecture and Components
  • High Availability Cluster Implementations
  • HDFS Component File System Namespace
  • Data Block Split
  • Data Replication Topology
  • HDFS Command Line
  • Yarn Introduction
  • Yarn Use Case
  • Yarn and Its Architecture
  • Resource Manager
  • How Resource Manager Operates
  • Application Master
  • How Yarn Runs an Application
  • Tools for Yarn Developers
  • Core components of Hadoop
  • Understanding Hadoop Master-Slave Architecture
  • Learn about NameNode, DataNode, Secondary Node
  • Understanding HDFS Architecture
  • Anatomy of Read and Write data on HDFS
  • MapReduce Architecture Flow
  • JobTracker and TaskTracker
  • Resource Manager and Node Manager

Module 3:  Hadoop Configuration

  • Hadoop Modes
  • Hadoop Terminal Commands
  • Cluster Configuration
  • Web Ports
  • Hadoop Configuration Files
  • Reporting, Recovery
  • MapReduce in Action

Module 4: Understanding Hadoop MapReduce Framework

  • Overview of the MapReduce Framework
  • Use cases of MapReduce
  • MapReduce Architecture
  • Anatomy of MapReduce Program
  • Mapper/Reducer Class, Driver code
  • Understand Combiner and Partitioner

Module 5: Advance MapReduce – Part 1

  • Write your own Partitioner
  • Writing Map and Reduce in Python
  • Map side/Reduce side Join
  • Distributed Join
  • Distributed Cache
  • Counters
  • Joining Multiple datasets in MapReduce

Module 6: Advance MapReduce – Part 2

  • MapReduce internals
  • Understanding Input Format
  • Custom Input Format
  • Using Writable and Comparable
  • Understanding Output Format
  • Sequence Files
  • JUnit and MRUnit Testing Frameworks

Module 7: Apache Pig

  • Apache Pig Introduction
  • Apache Pig Architecture
  • Apache Pig Installation
  • Apache Pig Execution
  • Apache Pig Grunt Shell
  • Apache Pig – Reading Data
  • Apache Pig – Storing Data
  • Apache Pig – Diagnostic Operator
  • Apache Pig – Describe Operator
  • Apache Pig – Explain Operator
  • Apache Pig – Illustrate Operator
  • Apache Pig – Group Operator
  • Apache Pig – Cogroup Operator
  • Apache Pig – Join Operator
  • Apache Pig – Cross Operator
  • Apache Pig – Union Operator
  • Apache Pig – Split Operator
  • Apache Pig – Filter Operator
  • Apache Pig – Distinct Operator
  • Apache Pig – Foreach Operator
  • Apache Pig – Order By
  • Apache Pig – Limit Operator
  • Apache Pig – Eval Functions
  • Apache Pig – Bag & Tuple Functions
  • Apache Pig – String Functions
  • Apache Pig – date-time Functions
  • Apache Pig – Math Functions

Module 8: Apache Hive and HiveQL

  • Hive – Introduction
  • Hive – Installation
  • Hive – Data Types
  • Hive – Create Database
  • Hive – Drop Database
  • Hive – Create Table
  • Hive – Alter Table
  • Hive – Drop Table
  • Hive – Partitioning
  • Hive – Built-In Operators
  • Hive – Built-In Functions
  • Hive – Views And Indexes
  • Difference between Hive and RDBMS

Module 9: Advance HiveQL

  • Multi-Table Inserts
  • Joins
  • Grouping Sets, Cubes, Rollups
  • Custom Map and Reduce scripts
  • Hive SerDe
  • Hive UDF
  • Hive UDAF
  • Hive Partitioning
  • Dynamic Partitioning in Hive
  • Hive Bucketing
  • Hive Partitioning and Bucketing together
  • Hive Data Sampling

Module 10: Apache Flume, Sqoop, Oozie

  • Sqoop – How Sqoop works
  • Sqoop Architecture
  • Flume – How it works
  • Flume Complex Flow – Multiplexing
  • Oozie – Simple/Complex Flow
  • Oozie Service/ Scheduler
  • Use Cases – Time and Data triggers

Module 11 NoSQL Databases

  • CAP theorem
  • RDBMS vs NoSQL
  • Key Value stores: Memcached, Riak
  • Key Value stores: Redis, Dynamo DB
  • Column Family: Cassandra, HBase
  • Graph Store: Neo4J
  • Document Store: MongoDB, CouchDB

Module 12 Apache HBase

  • When/Why to use HBase
  • HBase Architecture/Storage
  • HBase Data Model
  • HBase Families/ Column Families
  • HBase Master
  • HBase vs RDBMS
  • Access HBase Data
  • HBase – Overview
  • HBase – Architecture
  • HBase – Installation
  • HBase – Shell
  • HBase – General Commands
  • HBase – Admin API
  • HBase – Create Table
  • HBase – Listing Table
  • HBase – Disabling a Table
  • HBase – Enabling a Table
  • HBase – Describe & Alter
  • HBase – Exists
  • HBase – Drop a Table
  • HBase – Shutting Down
  • HBase – Client API
  • HBase – Create Data
  • HBase – Update Data
  • HBase – Read Data
  • HBase – Delete Data
  • HBase – Scan
  • HBase – Count & Truncate
  • HBase – Security

Module 13 Apache Zookeeper

  • What is Zookeeper
  • Zookeeper Data Model
  • ZNokde Types
  • Sequential ZNodes
  • Installing and Configuring
  • Running Zookeeper
  • Zookeeper use cases

Module 14 Hadoop 2.0, YARN, MRv2

  • Hadoop 1.0 Limitations
  • MapReduce Limitations
  • HDFS 2: Architecture
  • HDFS 2: High availability
  • HDFS 2: Federation
  • YARN Architecture
  • Classic vs YARN
  • YARN multitenancy
  • YARN Capacity Scheduler

Module 15: Basics of Functional Programming and Scala

  • Scala – Overview
  • Scala – Environment Setup
  • Scala – Basic Syntax
  • Scala – Data Types
  • Scala – Variables
  • Scala – Classes & Objects
  • Scala – Access Modifiers
  • Scala – Operators
  • Scala – IF ELSE
  • Scala – Loop Statements
  • Scala – Functions
  • Scala – Closures
  • Scala – Strings
  • Scala – Arrays
  • Scala – Collections
  • Scala – Traits
  • Scala – Pattern Matching
  • Scala – Regular Expressions
  • Scala – Exception Handling
  • Scala – Extractors
  • Scala – Files I/O

Module 16: Apache Spark Next-Generation Big Data Framework

  • History of Spark
  • Limitations of Mapreduce in Hadoop
  • Introduction to Apache Spark
  • Components of Spark
  • Application of In-memory Processing
  • Hadoop Ecosystem vs Spark
  • Advantages of Spark
  • Spark Architecture
  • Spark Cluster in Real World
  • Demo: Running a Scala Programs in Spark Shell
  • Demo: Setting Up Execution Environment in Ide
  • Demo: Spark Web UI
  • Apache Spark – Core Programming
  • Apache Spark – Deployment
  • Advanced Spark Programming

Module 17: Spark MLLib Modelling BigData with Spark

  • Spark Mllib Modeling Big Data With Spark
  • Role of Data Scientist and Data Analyst in Big Data
  • Analytics in Spark
  • Machine Learning
  • Supervised Learning
  • Demo: Classification of Linear Svm
  • Demo: Linear Regression With Real World Case Studies
  • Unsupervised Learning
  • Demo: Unsupervised Clustering K-means
  • Reinforcement Learning
  • Semi-supervised Learning
  • Overview of Mllib

Top Reasons to join Itronix Solutions for Big Data Hadoop Course in Jalandhar:

  • We provide video tutorials of the classroom sessions, so in case if the candidate missed any class he/she can learn from those video tutorials by Er Karan Arora
  • All our training programs are based on live case studies and industry oriented projects.
  • Our training curriculum is approved by our data scientists and placement partners.
  • Training/Coaching are going to be conducted on daily & weekly basis and conjointly.  We will customize the training schedule as per the candidate necessities.
  • We have one of the biggest team of certified expertise with 8+ years of real industry experience.
  • Training will be conducted by our Founder and Data Scientists.
  • Our Labs are terribly well-equipped with upgraded version of hardware and software.
  • Our classrooms are fully geared up with projectors, Smart Labs, Smart Tablets & Wi-Fi access.
  • We provide free personality development classes which includes Fluency, Group Discussions, Job interviews Preparation & Presentation skills.
  • You will get study material in form of E-Book’s, Jupyter Notebooks and 1500 Interview Questions.
  • Worldwide Recognized Course Completion Certificate by IBM, once you’ve completed the course.
  • Flexible Payment options such as Paytm, Cheques, Google Pay, Cash, Credit Card, UPI, Debit Card and Net Banking.
  • Big Data & Hadoop training in Jalandhar  is designed according to current IT Standards.
  • We offer the best Big Data & Hadoop training and placement in Mohali with well-defined training modules & curriculum
  • 24×7 lab facility. Students/Professionals are free to access the labs, Desktops for  as per their own preferred or suitable timings.

Itronix Solutions Placement Assistance

Being one of the top Big Data and Hadoop Training Company and a Certified Microsoft Authorized Educatation Partner, Cisco Partners, Intel Technology Provider, Google Certified Professionals & IBM Certified. Itronix Solutions deals with 100% Job Placements for Eligible Students after successful completion of the course.

  • Itronix Solutions helps to keep you updated with latest trends and technologies.
  • Itronix Solutions helps in updating your resume according to the job or company requirement
  • Itronix Solutions helps in providing placement assistance in top IT FIRMS. Many of our alumni are working in ValueCoders, ArStudiouz, PixelCrayons,Prolitus, Space-O Technologies, Technostacks Infotech Pvt. Ltd, Focaloid Technologies,RIT Solution, iPraxa Inc, Webtunix AI TCS, Amazon, Facebook, Sasken, CrossML, Infosys, Google, Uber and Wipro