Big Data Hadoop Course Overview

The Big Data and Hadoop Training in Los Angeles will equip you with in-depth knowledge of Big Data’s framework using tools such as Hadoop and Spark. With Big Data and Hadoop training in Los Angeles, students are given the opportunity toemploy the Integrated Lab to solve real-world, industry-relevent problems. This exercise provides Big Data work experience.

Big Data Hadoop Training Key Features

100% Money Back Guarantee
No questions asked refund*

At Simplilearn, we value the trust of our patrons immensely. But, if you feel that this Big Data Hadoop course does not meet your expectations, we offer a 7-day money-back guarantee. Just send us a refund request via email within 7 days of purchase and we will refund 100% of your payment, no questions asked!
  • 8X higher live interaction in live online classes by industry experts
  • Life time access to self paced content
  • 4 real-life industry projects using Hadoop, Hive and Big data stack
  • Training on Yarn, MapReduce, Pig, Hive, HBase, and Apache Spark
  • Aligned to Cloudera CCA175 certification exam

Skills Covered

  • Realtime data processing
  • Functional programming
  • Spark applications
  • Parallel processing
  • Spark RDD optimization techniques
  • Spark SQL

Benefits

Give your career the lift it needs by taking Big Data and Hadoop Training in Los Angeles. The opportunities are lucrative: the global HADOOP-AS-A-SERVICE (HAAS) Market in 2019 was USD 7.35 Billion and promises to keep growing.  Many believe the market will grow at a CAGR of 39.3%, increasing to USD 74.84 Billion by 2026. To remain relevant in the industry, Big Data and Hadoop Training in Los Angeles is important.

  • Designation
  • Annual Salary
  • Hiring Companies
  • Annual Salary
    $93KMin
    $124KAverage
    $165KMax
    Source: Glassdoor
    Hiring Companies
    Amazon hiring for Big Data Architect professionals in Los Angeles
    Hewlett-Packard hiring for Big Data Architect professionals in Los Angeles
    Wipro hiring for Big Data Architect professionals in Los Angeles
    Cognizant hiring for Big Data Architect professionals in Los Angeles
    Spotify hiring for Big Data Architect professionals in Los Angeles
    Source: Indeed
  • Annual Salary
    $81KMin
    $117KAverage
    $160KMax
    Source: Glassdoor
    Hiring Companies
    Amazon hiring for Big Data Engineer professionals in Los Angeles
    Hewlett-Packard hiring for Big Data Engineer professionals in Los Angeles
    Facebook hiring for Big Data Engineer professionals in Los Angeles
    KPMG hiring for Big Data Engineer professionals in Los Angeles
    Verizon hiring for Big Data Engineer professionals in Los Angeles
    Source: Indeed
  • Annual Salary
    $58KMin
    $88.5KAverage
    $128KMax
    Source: Glassdoor
    Hiring Companies
    Cisco hiring for Big Data Developer professionals in Los Angeles
    Target Corp hiring for Big Data Developer professionals in Los Angeles
    GE hiring for Big Data Developer professionals in Los Angeles
    IBM hiring for Big Data Developer professionals in Los Angeles
    Source: Indeed

Training Options

Self-Paced Learning

$ 899

  • Lifetime access to high-quality self-paced eLearning content curated by industry experts
  • 5 hands-on projects to perfect the skills learnt
  • 2 simulation test papers for self-assessment
  • 4 Labs to practice live during sessions
  • 24x7 learner assistance and support

online Bootcamp

$ 999

  • Everything in Self-Paced Learning, plus
  • 90 days of flexible access to online classes
  • Live, online classroom training by top instructors and practitioners
  • Classes starting in Los Angeles from:-
3rd Oct: Weekday Class
5th Nov: Weekend Class
Show all classes

Corporate Training

Customized to your team's needs

  • Customized learning delivery model (self-paced and/or instructor-led)
  • Flexible pricing options
  • Enterprise grade learning management system (LMS)
  • Enterprise dashboards for individuals and teams
  • 24x7 learner assistance and support

Big Data Hadoop Course Curriculum

Eligibility

This Big Data and Hadoop Course in Los Angeles is perfect for data management, analytics, and IT professionals who are ready to expand their talents to include Big Data Hadoop. This Big Data and Hadoop training in Los Angeles course is beneficial for project software developers and architects, analytics and business intelligence professionals, data management professionals, testing and mainframe professionals, senior IT professionals, and managers. The Big Data and Hadoop Course in Los Angeles is also useful for aspiring Data Scientists and general graduates looking to start a career in Big Data Analytics
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Pre-requisites

Before starting the Big Data and Hadoop training in Los Angeles, you should possess a basic understanding of Core Java and SQL. Professionals can sharpen their foundational Java skills with Simplilearn, which provides Java essentials for Hadoop — included in its Big Data and Hadoop course in Los Angeles.
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Course Content

  • Free Course
  • Core Java

    Preview
    • Lesson 01: Introduction to Java 11 and OOPs Concepts

      03:45:02Preview
      • 1.01 Course Introduction
        13:40
      • 1.02 Learning Objectives
        01:26
      • 1.03 Introduction
        04:39
      • 1.04 Working of Java program
        06:24
      • 1.05 Object Oriented Programming
        08:58
      • 1.06 Install and Work with Eclipse
        05:29
      • 1.07 Demo - Basic Java Program
        14:25
      • 1.08 Demo - Displaying Content
        14:28
      • 1.09 Basic Elements of Java 
        00:43
      • 1.10 Unicode Characters
        01:38
      • 1.11 Variables
        06:33
      • 1.12 Data Types
        06:48
      • 1.13 Operators
        06:57
      • 1.14 Operator (Logical Operator)
        05:03
      • 1.15 Operators Precedence
        01:01
      • 1.16 Type Casting or Type Conversion
        02:54
      • 1.17 Conditional Statements
        07:17
      • 1.18 Conditional Statement (Nested if)
        03:19
      • 1.19 Loops
        03:22
      • 1.20 for vs while vs do while
        08:21
      • 1.21 Access Specifiers
        04:22
      • 1.22 Java Eleven
        01:22
      • 1.23 Null, this, and instanceof Operators
        03:00
      • 1.24 Destructors
        02:10
      • 1.25 Code Refactoring
        02:36
      • 1.26 Garbage Collector
        01:35
      • 1.27 Static Code Analysis
        01:31
      • 1.28 String
        03:32
      • 1.29 Arrays Part One
        06:06
      • 1.30 Arrays Part Two
        06:48
      • 1.31 For – Each Loop
        05:43
      • 1.32 Method Overloading
        06:11
      • 1.33 Command Line Arguments
        03:46
      • 1.34 Parameter Passing Techniques
        01:38
      • 1.35 Types of Parameters
        02:51
      • 1.36 Variable Arguments
        04:51
      • 1.37 Initializer
        03:24
      • 1.38 Demo - String Functions Program
        16:33
      • 1.39 Demo - Quiz Program
        16:49
      • 1.40 Demo - Student Record and Displaying by Registration Number Program
        04:36
      • 1.41 Summary
        02:13
    • Lesson 02: Utility Packages and Inheritance

      01:27:27Preview
      • 2.01 Learning Objectives
        00:41
      • 2.02 Packages in Java
        06:05
      • 2.04 Inheritance in Java
        06:50
      • 2.05 Object Type Casting in Java
        05:03
      • 2.06 Methоd Оverriding in Java
        03:00
      • 2.07 Lambda Expression in Java
        03:35
      • 2.08 Static Variables and Methods
        03:49
      • 2.09 Abstract Classes
        01:37
      • 2.10 Interface in Java
        03:31
      • 2.11 Jаvа Set Interfасe
        03:07
      • 2.12 Marker Interfaces in Java
        01:25
      • 2.13 Inner Class
        02:43
      • 2.14 Exception Handling in Java
        09:59
      • 2.15 Java Memory Management
        01:14
      • 2.03 Demo - Utility Packages Program
        09:58
      • 2.17 Demo - Bank Account Statement using Inheritance
        09:14
      • 2.18 Demo - House Architecture using Polymorphism Program
        06:09
      • 2.16 Demo - Creating Errors and Catching the Exception Program
        07:53
      • 2.19 Summary
        01:34
    • Lesson 03: Multithreading Concepts

      03:00:10Preview
      • 3.01 Learning Objectives
        01:54
      • 3.02 Multithreading
        04:18
      • 3.03 Introduction to Threads
        09:32
      • 3.04 Thread Life Cycle
        01:54
      • 3.05 Thread Priority
        02:12
      • 3.06 Deamon Thread in Java
        01:06
      • 3.07 Thread Scheduling and Sleeping
        03:15
      • 3.08 Thread Synchronization
        07:35
      • 3.09 Wrapper Classes
        03:46
      • 3.10 Autoboxing and Unboxing
        08:32
      • 3.11 java.util and java.lang Classes
        07:48
      • 3.12 java.lang - String Class
        05:04
      • 3.13 java.util - StringBuilder and StringTokenizer Class
        04:30
      • 3.14 java.lang - Math Class
        02:02
      • 3.15 java.util - Locale Class
        04:56
      • 3.16 Jаvа Generics
        06:12
      • 3.17 Collections Framework in Java
        05:55
      • 3.18 Set Interface in Collection
        01:30
      • 3.19 Hashcode() in Collection
        01:29
      • 3.20 List in Collections 
        03:53
      • 3.21 Queue in Collections 
        03:31
      • 3.22 Соmраrаtоr Interfасe in Collections
        03:22
      • 3.23 Deque in Collections
        02:04
      • 3.24 Map in Collections
        05:38
      • 3.25 For - Each Method in Java
        00:42
      • 3.26 Differentiate Collections and Array Class 
        02:37
      • 3.27 Input or Output Stream
        03:01
      • 3.28 Java.io.file Class
        04:15
      • 3.29 Byte Stream Hierarchy
        08:49
      • 3.30 CharacterStream Classes
        01:50
      • 3.31 Serialization
        01:51
      • 3.32 JUnit 
        01:06
      • 3.33 Logger - log4j
        03:52
      • 3.34 Demo - Creating and Sorting Students Regno using Arrays
        14:44
      • 3.35 Demo - Stack Queue and Linked List Programs
        24:18
      • 3.36 Demo - Multithreading Program
        09:44
      • 3.37 Summary
        01:23
    • Lesson 04: Debugging Concepts

      01:11:20Preview
      • 4.01 Learning Objectives
        00:56
      • 4.02 Java Debugging Techniques 
        05:25
      • 4.03 Tracing and Logging Analysis 
        07:50
      • 4.04 Log Levels and Log Analysis
        09:47
      • 4.05 Stack Trace
        04:29
      • 4.06 Logging using log4j
        03:45
      • 4.07 Best Practices of log4j Part - One
        08:54
      • 4.08 Best Practices of log4j Part - Two
        09:18
      • 4.09 log4j Levels
        01:04
      • 4.10 Eclipse Debugging Support
        02:18
      • 4.11 Setting Breаkроints
        00:31
      • 4.12 Stepping Through or Variable Inspection
        02:41
      • 4.13 Demo - Analysis of Reports with Logging
        13:06
      • 4.14 Summary
        01:16
    • Lesson 05: JUnit

      01:50:25Preview
      • 5.01 Learning Objectives
        00:33
      • 5.02 Introduction
        06:07
      • 5.03 Unit Testing
        03:40
      • 5.04 JUnit Test Framework
        08:16
      • 5.05 JUnit Test Framework - Annotations
        07:12
      • 5.06 JUnit Test Framework - Assert Class
        05:49
      • 5.07 JUnit Test Framework - Test Suite
        03:49
      • 5.08 JUnit Test Framework - Exceptions Test
        04:14
      • 5.10 Demo - Generating Report using JUnit
        29:40
      • 5.09 Demo - Testing Student Mark System with JUnit
        40:00
      • 5.11 Summary
        01:05
    • Lesson 06: Java Cryptographic Extensions

      01:11:38Preview
      • 6.01 Learning Objectives
        00:40
      • 6.02 Cryptography
        09:22
      • 6.03 Two Types of Authenticators
        04:32
      • 6.04 CHACHA20 Stream Cipher and Poly1305 Authenticator
        06:16
      • 6.05 Example Program
        08:13
      • 6.06 Demo - Cryptographic Program
        41:48
      • 6.07 Summary
        00:47
    • Lesson 07: Design Pattern

      03:18:20Preview
      • 7.01 Learning Objectives
        00:36
      • 7.02 Introduction of Design Pattern
        05:22
      • 7.03 Types of Design Patterns
        00:24
      • 7.04 Creational Patterns
        01:21
      • 7.05 Fасtоry Method Раttern
        08:07
      • 7.07 Singletоn Design Раttern
        08:09
      • 7.08 Builder Pattern
        05:53
      • 7.09 Struсturаl Раtterns
        02:24
      • 7.10 Adарter Раttern
        04:42
      • 7.11 Bridge Раttern
        07:39
      • 7.12 Fасаde Раttern
        07:00
      • 7.13 Flyweight Design Раttern
        07:25
      • 7.14 Behаviоrаl Design Раtterns
        01:46
      • 7.15 Strategy Design Pattern
        05:03
      • 7.15 Сhаin оf Resроnsibility Раttern
        03:51
      • 7.16 Command Design Pattern
        05:17
      • 7.17 Interрreter Design Раttern
        03:47
      • 7.18 Iterаtоr Design Раttern
        05:25
      • 7.19 Mediаtоr Design Pаttern
        06:19
      • 7.20 Memento Design Раttern
        03:55
      • 7.21 Null Object Design Pattern
        05:11
      • 7.22 Observer Design Pattern
        04:19
      • 7.23 State Design Pattern
        06:39
      • 7.24 Template Method Design Pattern
        03:35
      • 7.25 Visitor Design Pattern
        05:25
      • 7.26 JEE or J2EE Design Patterns
        04:01
      • 7.27 Demo - Loan Approval Process using One of Behavioural Design Pattern
        30:04
      • 7.06 Demo - Creating Family of Objects using Factory Design Pattern
        22:42
      • 7.28 Demo - State Design Pattern Program
        20:55
      • 7.29 Summary
        01:04
  • Free Course
  • Linux Training

    Preview
    • Lesson 01 - Course Introduction

      05:15Preview
      • 1.01 Course Introduction
        05:15
    • Lesson 02 - Introduction to Linux

      04:35Preview
      • 2.01 Introduction
        00:38
      • 2.02 Linux
        01:03
      • 2.03 Linux vs. Windows
        01:18
      • 2.04 Linux vs Unix
        00:30
      • 2.05 Open Source
        00:26
      • 2.06 Multiple Distributions of Linux
        00:25
      • 2.07 Key Takeaways
        00:15
      • Knowledge Check
      • Exploration of Operating System
    • Lesson 03 - Ubuntu

      16:24Preview
      • 3.01 Introduction
        00:30
      • 3.02 Ubuntu Distribution
        00:23
      • 3.03 Ubuntu Installation
        10:53
      • 3.04 Ubuntu Login
        01:36
      • 3.05 Terminal and Console
        00:57
      • 3.06 Kernel Architecture
        01:44
      • 3.07 Key Takeaways
        00:21
      • Knowledge Check
      • Installation of Ubuntu
    • Lesson 04 - Ubuntu Dashboard

      17:53Preview
      • 4.01 Introduction
        00:38
      • 4.02 Gnome Desktop Interface
        01:30
      • 4.03 Firefox Web Browser
        00:56
      • 4.04 Home Folder
        01:00
      • 4.05 LibreOffice Writer
        00:50
      • 4.06 Ubuntu Software Center
        01:54
      • 4.07 System Settings
        06:04
      • 4.08 Workspaces
        01:20
      • 4.09 Network Manager
        03:23
      • 4.10 Key Takeaways
        00:18
      • Knowledge Check
      • Exploration of the Gnome Desktop and Customization of Display
    • Lesson 05 - File System Organization

      31:22Preview
      • 5.01 Introduction
        00:43
      • 5.02 File System Organization
        01:55
      • 5.03 Important Directories and Their Functions
        06:31
      • 5.04 Mount and Unmount
        04:04
      • 5.05 Configuration Files in Linux (Ubuntu)
        02:06
      • 5.06 Permissions for Files and Directories
        05:17
      • 5.07 User Administration
        10:21
      • 5.08 Key Takeaways
        00:25
      • Knowledge Check
      • Navigation through File Systems
    • Lesson 06 - Introduction to CLI

      01:15:45Preview
      • 6.01 Introduction
        00:43
      • 6.02 Starting Up the Terminal
        02:45
      • 6.03 Running Commands as Superuser
        03:58
      • 6.04 Finding Help
        02:00
      • 6.05 Manual Sections
        03:17
      • 6.06 Manual Captions
        04:03
      • 6.07 Man K Command
        03:07
      • 6.08 Find Command
        02:03
      • 6.09 Moving Around the File System
        05:04
      • 6.10 Manipulating Files and Folders
        08:17
      • 6.11 Creating Files and Directories
        03:29
      • 6.12 Copying Files and Directories
        07:44
      • 6.13 Renaming Files and Directories
        02:34
      • 6.14 Moving Files and Directories
        04:41
      • 6.15 Removing Files and Directories
        02:25
      • 6.16 System Information Commands
        03:20
      • 6.17 Free Command
        02:14
      • 6.18 Top Command
        05:01
      • 6.19 Uname Command
        02:12
      • 6.20 Lsb Release Command
        01:09
      • 6.21 IP Command
        02:40
      • 6.22 Lspci Command
        01:31
      • 6.23 Lsusb Command
        01:02
      • 6.24 Key Takeaways
        00:26
      • Knowledge Check
      • Exploration of Manual Pages
    • Lesson 07 - Editing Text Files and Search Patterns

      27:19Preview
      • 7.01 Introduction
        00:34
      • 7.02 Introduction to vi Editor
        00:43
      • 7.03 Create Files Using vi Editor
        08:18
      • 7.04 Copy and Cut Data
        02:30
      • 7.05 Apply File Operations Using vi Editor
        01:33
      • 7.06 Search Word and Character
        03:47
      • 7.07 Jump and Join Line
        03:35
      • 7.08 grep and egrep Command
        06:01
      • 7.09 Key Takeaways
        00:18
      • Knowledge Check
      • Copy and Search Data
    • Lesson 08 - Package Management

      26:06Preview
      • 8.01 Introduction
        00:36
      • 8.02 Repository
        03:46
      • 8.03 Repository Access
        07:12
      • 8.04 Introduction to apt get Command
        05:33
      • 8.05 Update vs. Upgrade
        02:28
      • 8.06 Introduction to PPA
        06:03
      • 8.07 Key Takeaways
        00:28
      • Knowledge Check
      • Check for Updates
    • Practice Project

      • Ubuntu Installation

Industry Project

  • Project 1

    Analyzing Historical Insurance claims

    Use Hadoop features to predict patterns and share actionable insights for a car insurance company.

  • Project 2

    Analyzing Intraday price changes

    Use Hive features for data engineering and analysis of New York stock exchange data.

  • Project 3

    Analyzing employee sentiment

    Perform sentiment analysis on employee review data gathered from Google, Netflix, and Facebook.

  • Project 4

    Analyzing Product performance

    Perform product and customer segmentation to increase the sales of Amazon.

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Big Data Hadoop Course Advisor

  • Ronald van Loon

    Ronald van Loon

    CEO, Principal Analyst Intelligent World,Top10 AI-Data-IoT-Influencer

    Named by Onalytica as one of the three most influential people in Big Data, Ronald is also an author of a number of leading Big Data and Data Science websites, including Datafloq, Data Science Central, and The Guardian. He also regularly speaks at renowned events.

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Big Data Hadoop Exam & Certification

Big Data Hadoop Certificate in Los Angeles
  • What do I need to do to unlock my Simplilearn's Big Data Hadoop Certificate?

    Online Classroom:

    • Attend one complete batch
    • Complete one project and one simulation test with a minimum score of 80%

    Online Self-Learning:

    • Complete 85% of the course
    • Complete one project and one simulation test with a minimum score of 80%

  • How will I become Certified Hadoop Developer in Los Angeles?

    To become Certified Big Data Hadoop Developer, you must fulfill both of the following criteria:

    • Successfully Complete SimpliLearns Hadoop certification training Course that helps you mastering all the tasks of Hadoop developer.
    • Pass Spark and Hadoop Developer Exam(CCA175) with a minimum score of 70%. The simulation test is an online exam and that must be answered within 120 minutes
       

  • What is the Duration of this Hadoop Training?

    Simplilearn’s Hadoop Certifications Training in Los Angeles is Classroom Flexi-Pass Learning Methodology that has a validity of 180 days (6 months) of high-quality e-learning videos, Self-paced learning Content plus 90 days of access to 9+ instructor-led online training classes.

  • How Much does this Course Cost's in Los Angeles?

    Simplilearn’s Hadoop Certification course in Los Angeles is priced at $999 for Online Classroom Flexi-Pass.

  • What are the prerequisites to learn Big Data Hadoop?

    There are no prerequisites for learning this course. However, knowledge of Core Java and SQL will be beneficial, but certainly not a mandate. If you wish to brush up your Core-Java skills, Simplilearn offers a complimentary self-paced course "Java essentials for Hadoop" when you enroll for this course. For Spark, this course uses Python and Scala, and an e-book is provided to support your learning.
     

  • How long does it take to complete the Big Data and Hadoop Training in Los Angeles?

    It takes around 45-50 hours to successfully complete the Big Data and Hadoop training in Los Angeles.

  • How many attempts do I get to pass the Big Data Hadoop certification exam?

    A goal of Simplilearn's Big Data and Hadoop training in Los Angeles is to make sure its enrollees are prepared to pass the CCA175 Hadoop certification exam on the first attempt. However, if you do fail, you still have a maximum of three additional attempts to successfully pass.

  • How long does it take to be eligible for this exam?

    Upon completion of the Big Data Hadoop course, you will receive the Big Data Hadoop certificate immediately.

  • How long is the certificate from the Simplilearn Big Data and Hadoop course in Los Angeles valid for?

    It never expires. The Big Data and Hadoop training in Los Angeles certification from Simplilearn has lifetime validity.

  • If I do fail the CCA175 Hadoop certification exam, how soon can I retake it?

    Students who finish the Big Data and Hadoop course in Los Angeles and subsequently fail the CCA175 Hadoop certification exam are required to wait 30 days before taking the test again.

  • If I pass the CCA175 Hadoop certification exam, when and how do I receive a certificate?

    Once a graduate successfully passes their CCA175 Hadoop certification exam, they will get an email a couple of days later that includes their digital certificate and certification license number.

  • Who provides certification?

    Simplilearn will award you a certificate for completing the Big Data and Hadoop course in Los Angeles. Once you finish the Big Data and Hadoop training in Los Angeles, you need to pass the Cloudera exam in order to get a CCA175 - Spark and Hadoop certificate from Cloudera.

  • How do I become a Big Data Engineer?

    The Big Data and Hadoop training in Los Angeles readies you for success in your Big Data Engineer role by giving you insights into Hadoop’s ecosystem in addition to various Big Data tools and methodologies. The Simplilearn completion certificate for the Big Data and Hadoop course in Los Angeles attests to your new Big Data skills and relevant on-the-job expertise. This Big Data and Hadoop course in Los Angeles provides data engineering expert training by offering instruction on Hadoop tools such as HDFS, HBase, Hive, MapReduce, Kafka, Flume, and more.

  • How do I unlock the Simplilearn’s Big Data Hadoop training course completion certificate?

    Online Classroom: Attend one complete batch of Big Data and Hadoop training in Los Angeles, finish one project, and pass one simulation test with a score of at least 80%.
    Online Self-learning: Finish 85% of the Big Data and Hadoop course in Los Angeles, finish one project, and pass one simulation test with a score of at least 80%.

  • How much does the CCA175 Hadoop certification cost?

    The CCA 175 Spark and Hadoop Developer exam costs USD 295.

  • Do you offer any practice tests as part of the course?

    Yes, the Big Data and Hadoop training in Los Angeles provides one practice test to help you prepare for the CCA175 Hadoop certification exam. You can take this free Big Data and Hadoop Developer Practice Test to get a better idea of the kind of tests included in the course curriculum.

Big Data Hadoop Course Reviews

  • Solomon Larbi Opoku

    Solomon Larbi Opoku

    Senior Desktop Support Technician, Washington

    Content looks comprehensive and meets industry and market demand. The combination of theory and practical training is amazing.

  • Navin Ranjan

    Navin Ranjan

    Assistant Consultant, Gaithersburg

    Faculty is very good and explains all the things very clearly. Big data is totally new to me so I am not able to understand a few things but after listening to recordings I get most of the things.

  • Joan Schnyder

    Joan Schnyder

    Business, Systems Technical Analyst and Data Scientist, New York City

    The pace is perfect! Also, trainer is doing a great job of answering pertinent questions and not unrelated or advanced questions.

  • Ludovick Jacob

    Ludovick Jacob

    Manager of Enterprise Database Engineering & Support at USAC, Washington

    I really like the content of the course and the way trainer relates it with real-life examples.

  • Puviarasan Sivanantham

    Puviarasan Sivanantham

    Data Engineer at Fanatics, Inc., Sunnyvale

    Dedication of the trainer towards answering each & every question of the trainees makes us feel great and the online session as real as a classroom session.

  • Richard Kershner

    Richard Kershner

    Software Developer, Colorado Springs

    The trainer was knowledgeable and patient in explaining things. Many things were significantly easier to grasp with a live interactive instructor. I also like that he went out of his way to send additional information and solutions after the class via email.

  • Aaron Whigham

    Aaron Whigham

    Business Analyst at CNA Surety, Chicago

    Very knowledgeable trainer, appreciate the time slot as well… Loved everything so far. I am very excited…

  • Rudolf Schier

    Rudolf Schier

    Java Software Engineer at DAT Solutions, Portland

    Great approach for the core understanding of Hadoop. Concepts are repeated from different points of view, responding to audience. At the end of the class you understand it.

  • Kinshuk Srivastava

    Kinshuk Srivastava

    Data Scientist at Walmart, Little Rock

    The course is very informative and interactive and that is the best part of this training.

  • Priyanka Garg

    Priyanka Garg

    Sr. Consultant, Detroit

    Very informative and active sessions. Trainer is easy going and very interactive.

  • Peter Dao

    Peter Dao

    Senior Technical Analyst at Sutter Health, Sacramento

    The content is well designed and the instructor was excellent.

  • Anil Prakash Singh

    Anil Prakash Singh

    Project Manager/Senior Business Analyst @ Tata Consultancy Services, Honolulu

    The trainer really went the extra mile to help me work along. Thanks

  • Dipto Mukherjee

    Dipto Mukherjee

    Etl Lead at Syntel, Phoenix

    Excellent learning experience. The training was superb! Thanks Simplilearn for arranging such wonderful sessions.

  • Shubhangi Meshram

    Shubhangi Meshram

    Senior Technical Associate at Tech Mahindra, Philadelphia

    I am impressed with the overall structure of training, like if we miss class we get the recording, for practice we have CloudLabs, discussion forum for subject clarifications, and the trainer is always there to answer.

  • Sashank Chaluvadi

    Sashank Chaluvadi

    Houston

    Very good course and a must for those who want to have a career in Quant.

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Why Online Bootcamp

  • Develop skills for real career growthCutting-edge curriculum designed in guidance with industry and academia to develop job-ready skills
  • Learn from experts active in their field, not out-of-touch trainersLeading practitioners who bring current best practices and case studies to sessions that fit into your work schedule.
  • Learn by working on real-world problemsCapstone projects involving real world data sets with virtual labs for hands-on learning
  • Structured guidance ensuring learning never stops24x7 Learning support from mentors and a community of like-minded peers to resolve any conceptual doubts

Big Data Hadoop Training FAQs

  • Why learn Big Data Hadoop with certification?

    The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025, so this is the perfect time to pursue a career in this field.

    The world is getting increasingly digital, and this means big data is here to stay. The importance of big data and data analytics is going to continue growing in the coming years. Choosing a career in the field of big data and analytics might be the type of role that you have been trying to find to meet your career expectations. Professionals who are working in this field can expect an impressive salary, the median salary for a data engineer is $137,776, with more than 130K jobs in this field worldwide. As more and more companies realize the need for specialists in big data and analytics, the number of these jobs will continue to grow. A role in this domain places you on the path to an exciting, evolving career that is predicted to grow sharply into 2025 and beyond.

  • What are the learning objectives?

    According to Forbes, Big Data & Hadoop Market is expected to reach $99.31B by 2022.
    This Big Data Hadoop certification course in Los Angeles is designed to give you an in-depth knowledge of the Big Data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. You will learn to use Pig, Hive, and Impala to process and analyze large datasets stored in the HDFS, and use Sqoop, Flume, and Kafka for data ingestion with our significant data training.

     

    You will master Spark and its core components, learn Spark’s architecture, and use the Spark cluster in real-world - Development, QA, and Production. With our Big Data Hadoop course, you will also use Spark SQL to convert RDDs to DataFrames and Load existing data into a DataFrame.

     

    As a part of the Big Data Hadoop course, you will be required to execute real-life, industry-based projects using Integrated Lab in the domains of Human Resource, Stock Exchange, BFSI, and Retail & Payments. This Big Data Hadoop training course in Los Angeles will also prepare you for the Cloudera CCA175 significant Hadoop certification exam.

  • What skills will you learn in this Big Data Hadoop training?

    Big Data Hadoop certification training in Los Angeles will enable you to master the concepts of the Hadoop framework and its deployment in a cluster environment. By the end of this course, you will be able to:

    • Learn how to navigate the Hadoop Ecosystem and understand how to optimize its use
    • Ingest data using Sqoop, Flume, and Kafka
    • Implement partitioning, bucketing, and indexing in Hive
    • Work with RDD in Apache Spark
    • Process real-time streaming data
    • Perform DataFrame operations in Spark using SQL queries
    • Implement User-Defined Functions (UDF) and User-Defined Attribute Functions (UDAF) in Spark
    • Prepare for Cloudera CCA175 Big Data certification exam

  • Who should take this Big Data Hadoop training course?

    Big Data career opportunities are on the rise, and Hadoop is quickly becoming a must-know technology in Big Data architecture. Big Data training in Los Angeles is best suited for IT, data management, and analytics professionals looking to gain expertise in Big Data, including:

    • Software Developers and Architects
    • Analytics Professionals
    • Senior IT professionals
    • Testing and Mainframe Professionals
    • Data Management Professionals
    • Business Intelligence Professionals
    • Project Managers
    • Aspiring Data Scientists
    • Graduates looking to build a career in Big Data Analytics

  • What projects are included in this Big Data Hadoop online training course?

    The Big Data Hadoop Training course in Los Angeles includes four real-life, industry-based projects. Following are the projects that you will be working on:

    Project 1: Analyzing employee sentiment

    Objective: To use Hive features for data analysis and sharing the actionable insights into the HR team for taking corrective actions.

    Domain: Human Resource

    Background of the problem statement: The HR team is surfing social media to gather current and ex-employee feedback or sentiments. This information gathered will be used to derive actionable insights and take corrective actions to improve the employer-employee relationship. The data is web-scraped from Glassdoor and contains detailed reviews of 67K employees from Google, Amazon, Facebook, Apple, Microsoft, and Netflix.

     

    Project 2: Analyzing Intraday price changes

    Objective: To use hive features for data engineering or analysis and sharing the actionable insights.

    Domain: Stock Exchange

    Background of the problem statement: NewYork stock exchange data of seven years, between 2010 to 2016, is captured for 500+ listed companies. The data set comprises of intra-day prices and volume traded for each listed company. The data serves both for machine learning and exploratory analysis projects, to automate the trading process and to predict the next trading-day winners or losers. The scope of this project is limited to exploratory data analysis.

     

    Project 3: Analyzing Historical Insurance claims

    Objective: To use the Hadoop features for data engineering or analysis of car insurance, share patterns, and actionable insights.

    Domain: BFSI

    Background of the problem statement: A car insurance company wants to look at its historical data to understand and predict the probability of a customer making a claim based on multiple features other than MVR_POINTS. The data set comprises 10K plus submitted claim records and 14 plus features. The scope of this project is limited to data engineering and analysis.
     

    Project 4: Analyzing Product performance

    Objective: To use the Big data stack for data engineering for the analysis of transactions, share patterns, and actionable insights.

    Domain: Retail & Payments

    Background of the problem statement: Amazon wants to launch new digital marketing campaigns for various categories for different brands to come up with new Christmas deal to:

    1. Increase their sales by a certain percentage.
    2. Promote products which are the least selling
    3. Promote products which are giving more profits

    They have provided a transactional data file that contains historical transactions of a few years along with product details across multiple categories. As an analytics consultant, your responsibility is to provide valuable product and customer insights to the marketing, sales, and procurement teams. You have to preprocess unstructured data into structured data and provide various statistics across products or brands or categories segments and tell which of these segments will increase the sales by performing well and, which segments need an improvement. The scope of this project is limited to data engineering and analysis.

  • How will Big Data training help your career?

    The field of big data and analytics is a dynamic one, adapting rapidly as technology evolves over time. Those professionals who take the initiative and excel in big data and analytics are well-positioned to keep pace with changes in the technology space and fill growing job opportunities. Some trends in big data include:

    • Global Hadoop Market to Reach $84.6 Billion by 2021 – Allied Market Research
    • The global Big Data and data engineering services market is expected to grow at a CAGR of 31.3 percent by 2025
    • Big Data & Hadoop Market is expected to reach $99.31B by 2022 - Forbes
    • Hadoop Administrators in the US receive salaries of up to $123,000 – indeed.com

  • What types of jobs are ideal for Big Data Hadoop certified professionals?

    Upon completion of the Big Data Hadoop training course in Los Angeles, you will have the skills required to help you land your dream job, including:

    • Data scientist
    • Data engineer
    • Data analyst
    • Project manager
    • Program manager

  • What are the Big Data Hadoop job opportunities in the Los Angeles?

    Big Data jobs in Los Angeles are present a dime a dozen, which spells good news for professionals. A quick search on Indeed will tell you that over 17000+ big data jobs across the country are posted on this platform alone. With a Big Data certificate, you could choose from various designations. Here’s a list of Big Data roles:

    • Data analyst
    • Data scientist
    • Big Data testing engineer
    • Big Data Engineer
    • Data Architect

  • What is the market trend for Hadoop in the Los Angeles?

    According to Forrester, Hadoop’s utilization in an organization increases by 32.9% every year. Similarly, a survey conducted in 2017 states the impending importance of data discovery and data visualization in organizations across the globe. According to this report, big data will play a significant role in all decisions made by organizations in the future. According to Payscale, a big data analyst specializing in Hadoop can earn up to $140,000. If this salary trend is anything to go by, then the demand for data professionals has never been higher.

  • Which companies in the Los Angeles are offering jobs in Hadoop?

    Several companies in Los Angeles are on the lookout for Big Data professionals. According to Indeed, some of the top companies looking out for big data professionals in Los Angeles are IBM, Google, Experian, NASA, Deloitte, Bank of America, Amazon, Cognizant,  etc.

  • What is the salary of a Hadoop Developer in Los Angeles?

    According to ZipRecruiter, entry-level big data professionals in the U.S. can earn $93,000 per year. However, a big data professional with experience can earn up to $153,000 in California. However, this salary can go up to $180,000.

  • What are the system requirements for this Big Data Course?

    The tools you’ll need to attend Big Data Hadoop training are:

    • Windows: Windows XP SP3 or higher
    • Mac: OSX 10.6 or higher
    • Internet speed: Preferably 512 Kbps or higher
    • Headset, speakers, and microphone: You’ll need headphones or speakers to hear instructions clearly, as well as a microphone to talk to others. You can use a headset with a built-in microphone, or separate speakers and microphone.

  • What are the modes of training offered for this Big Data course?

    We offer training for this Big Data course in the following modes:

    • Live Virtual Classroom or Online Classroom: Attend the Big Data course remotely from your desktop via video conferencing to increase productivity and reduce the time spent away from work or home.
    • Online Self-Learning: In this mode, you will access the video training and go through the Big Data course at your own convenience.

  • Can I cancel my enrollment? Do I get a refund?

    Yes, you can cancel your enrollment if necessary. We will refund the course price after deducting an administration fee. To learn more, you can view our Refund Policy.

  • Are there any group discounts for online classroom training programs?

    Yes, we have group discount options for our training programs. Contact us using the form on the right of any page on the Simplilearn website, or select the Live Chat link. Our customer service representatives can provide more details.

  • How do I enroll for the Big Data Hadoop certification training course?

    You can enroll for this Big Data Hadoop certification training course on our website and make an online payment using any of the following options:

    • Visa Credit or Debit Card
    • MasterCard
    • American Express
    • Diner’s Club
    • PayPal

    Once payment is received you will automatically receive a payment receipt and access information via email.

  • Who are our faculties and how are they selected?

    All of our highly qualified Hadoop certification trainers are industry Big Data experts with at least 10-12 years of relevant teaching experience in Big Data Hadoop. Each of them has gone through a rigorous selection process which includes profile screening, technical evaluation, and a training demo before they are certified to train for us. We also ensure that only those trainers with a high alumni rating continue to train for us.

  • What is Global Teaching Assistance?

    Our teaching assistants are a dedicated team of subject matter experts here to help you get certified in your first attempt. They engage students proactively to ensure the course path is being followed and help you enrich your learning experience, from class onboarding to project mentoring and job assistance. Teaching Assistance is available during business hours for this Big Data Hadoop training course.

  • What is covered under the 24/7 Support promise?

    We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your course with us to discuss Big Data and Hadoop topics.

  • If I am not from a programming background but have a basic knowledge of programming, can I still learn Hadoop?

    Yes, you can learn Hadoop without being from a software background. We provide complimentary courses in Java and Linux so that you can brush up on your programming skills. This will help you in learning Hadoop technologies better and faster.

  • What if I miss a class?

    • Simplilearn has Flexi-pass that lets you attend Big Data Hadoop course training classes to blend in with your busy schedule and gives you an advantage of being trained by world-class faculty with decades of industry experience combining the best of online classroom training and self-paced learning
    • With Flexi-pass, Simplilearn gives you access to as many as 15 sessions for 90 days

  • What are the other top Big Data Certification Courses Simplilearn is offering in Los Angeles city?

    Keeping up with the Big Data & Analytics boom, Simplilearn has tailored very comprehensive Big Data certification programs which ensures a complete development as a Big Data professional.

    Few of the courses offered around Big Data are:

    In addition to the above, Simpliearn has created Big Data Hadoop Architect Masters Program on Big Data which follows a curated learning path.

    Simplilearn also offers the following Masters program with respect to Data Science and Business Intelligence:

  • What is online classroom training for Big Data Course?

    Online classroom training for the Big Data Hadoop certification course is conducted via online live streaming of each class. The classes are conducted by a Big Data Hadoop certified trainer with more than 15 years of work and training experience.

  • Is this Big Data course a live training, or will I watch pre-recorded videos?

    If you enroll for self-paced e-learning, you will have access to pre-recorded videos. If you enroll for the online classroom Flexi Pass, you will have access to live Big Data Hadoop training conducted online as well as the pre-recorded videos.

  • Are the training and course material effective in preparing for the CCA175 Hadoop certification exam?

    Yes, Simplilearn’s Big Data Hadoop course and training materials are very much effective and will help you pass the CCA175 Hadoop certification exam.

  • What is Big data?

    Big data refers to a collection of extensive data sets, including structured, unstructured, and semi-structured data coming from various data sources and having different formats.These data sets are so complex and broad that they can't be processed using traditional techniques. When you combine big data with analytics, you can use it to solve business problems and make better decisions. 

  • What is Hadoop?

    Hadoop is an open-source framework that allows organizations to store and process big data in a parallel and distributed environment. It is used to store and combine data, and it scales up from one server to thousands of machines, each offering low-cost storage and local computation.

  • What is Spark?

    Spark is an open-source framework that provides several interconnected platforms, systems, and standards for big data projects. Spark is considered by many to be a more advanced product than Hadoop.

  • What is the Big Data concept?

    There are basically three concepts associated with Big Data - Volume, Variety, and Velocity. The volume refers to the amount of data we generate which is over 2.5 quintillion bytes per day, much larger than what we generated a decade ago. Velocity refers to the speed with which we receive data, be it real-time or in batches. Variety refers to the different formats of data like images, text, or videos.

  • How can beginners learn Big Data and Hadoop?

    Hadoop is one of the leading technological frameworks being widely used to leverage big data in an organization. Taking your first step toward big data is really challenging. Therefore, we believe it’s important to learn the basics about the technology before you pursue your certification. Simplilearn provides free resource articles, tutorials, and YouTube videos to help you to understand the Hadoop ecosystem and cover your basics. Our extensive course on Big Data Hadoop certification training will get you started with big data.

Our Los Angeles Correspondence / Mailing address

Simplilearn's Big Data Hadoop Certification Training Course in Los Angeles

10880 Wilshire Blvd., Suite 1101 Los Angeles, CA 90024 United States

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