Big Data Masters Program Training Course - Updated [April 2021] | ACTE
Home » Big Data Masters Program Training Course

Big Data Masters Program Training Course

(5.0) 7455 Ratings 9541Learners
  • Beginner & Advanced level Classes.
  • Hands-On Learning in Java.
  • Best Practice for interview Preparation Techniques in Big Data Technologies.
  • Lifetime Access for Student’s Portal, Study Materials, Videos & Top MNC Interview Question.
  • Affordable Fees with Best Curriculum Designed by Industrial Big Data Expert.
  • Delivered by 11+ years of Java Certified Expert | 12402+ Students Trained & 350+ Recruiting Clients.
  • Next Big Data Masters Program Training Batch to Begin this week – Enroll Your Name Now!

  • 135+ Hrs Hands On Training
  • 5 Live Projects For Hands-On Learning
  • 36+ Practical Assignments
  • 24/7 Students
  • Course Syllabus Java Essentials

    ₹ 12000
  • Course SyllabusSQL

    ₹ 12000
  • Course SyllabusLinux

    ₹ 14000
  • Course SyllabusBigData Hadoop

    ₹ 16000
  • Course SyllabusApache Spark & Scala

    ₹ 18000
  • Total Amount

    ₹ 72000
  • Discount Offered

    ₹ 21600
  • Amount To Pay

    ₹ 50400

Have Queries? Ask our Experts

+91 93833 99991

Available 24x7 for your queries

Upcoming Batches

12- APR- 2021
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session

14- APR- 2021
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

(Class 1Hr - 1:30Hrs) / Per Session

17- APR- 2021
Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

(Class 3hr - 3:30Hrs) / Per Session

17- APR- 2021
Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

(Class 4:30Hr - 5:00Hrs) / Per Session

Can't find a batch? Pick your own schedule

Outline of Big Data Masters Program Training

  • We train students for interviews and Offer Placements in top MNC companies.
  • Suitable for Graduates and Experienced Candidates from any Technical Background
  • You gain knowledge Big data advanced tools and exposure to industry best practices, Aptitude & SoftSkills
  • Experienced Trainers and Lab Facility
  • Big Data Hadoop Certification Guidance Support with Exam Dumps
  • For Corporate, we act as one stop recruiting partner. We provide right skilled candidates who are productive right from day one
  • Gudiance for Resume and Interviews Preparation Support
  • Learning Concepts: Java Essentials, Basics of SQL, LINUX, BigData Hadoop Guidance, Apache Spark & Scala
  • BEGIN YOUR CAREER WITH BIGDATA MASTER PROGRAM THAT LEADS YOU A JOB OFFER UPTO 5 LACS IN JUST 60 DAYS!
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

This is How ACTE Students Prepare for Better Jobs

PLACED IMAGE ACTE
Show More

About Big Data Masters Program Course

We would do whatever it takes to make this a definitive Big Data Masters Program course. We will try to cover almost all the topics related to Big Data Masters Program technology. This place would be your unique destination to learn Big Data Masters Program.

Learning Big Data Masters Program can help open up many opportunities for your career. It is a great skill-set to have as many roles in the job market requires proficiency in Freshers Masters. Mastering Big Data Masters Program can help you get started with your career in IT Companies like Paypal, Capgemini, Accenture, Mphasis, CTS and MindLabs, etc. are all hiring Big Data Analysts.

This course will not only cover the core issues but will also cover many more advanced topics. This course is going to be one of the most comprehensive Program course on ACTE. Dot Net, Java, Python, advanced topics PHP Essentials; THERE IS NO PROBLEM. Everything is covered.

Best Job Oriented Topics Covered
  • Java Essentials

    Basics of SQL

    Building Web Pages with PHP

  • Apache Spark & Scala

    Working with Forms and Form Data

    Working with Cookies and Sessions

  • LINUX

    BigData Hadoop

    Working with Cookies and Sessions

Big Data has the Familiarity to influence the IT industry with few new technologies or trends have done. It gives massive information caches that can help companies to improve their decision-making on another level.

Big Data is an opportunity to collect and preserve whatever data generation. There is a large amount of data floating around. It helps to improve the business, decisions making and providing a big edge over the competitors.

Big Data Analyst should have knowledge on large amount of data floating . This Specialization is designed primarily for data engineering professionals seeking to enter the fields as a Big Data Analyst.

We are happy and proud to say that we have a strong relationship with over 700+ small, mid-sized, and MNCs. Many of these companies have openings for Big Data Engineer. Moreover, we have a very active placement cell that provides 100% placement assistance to our students. The cell also contributes by training students in mock interviews and discussions even after the course completion.

It is easy to become a Big Data Engineer mainly focused on a lot of data floating helps the organization made the Decision on handling the data. It just needs to be able to recognize, understand, prioritize and apply data with Hadoop technologies.

  • Basics of Java.
  • Basic of SQL Programming.
  • Linux Commands.
  • BigData Hadoop Guidance.
  • Apache Spark & Scala.

Big Data Engineer should know the basic concepts of SQL programming languages and Hadoop technologies. Knowledge of various cloud technology is another need for Analysts.

Our courseware Program gives a hands-on approach to the students in Big Data Masters Program. This course deals with theory classes that teach the basics of modules followed by high intensity, Practical Sessions reflecting the current challenges that fulfill the Industrial Needs.

The salary offered is often very high for data engineering professionals. There are a variety of opportunities available across many domains. In this field, you can be an attractive one for the professionals looking for a sharp growth and learning curve in their career.

Three-Four months is long enough to learn a considerable amount of Big Data Masters Program. If the concern already knowing the basics of SQL Programming language, then two months would be a generous amount of time to learn enough Big Data Masters Program meaningfully contribute in a professional capacity.

Top reasons to consider a career in Big Data Masters Program?

  • Creative Flexibility. You know about multiple aspects of development.
  • Better Productivity.
  • High Demand. The demand for Big Data Masters Program is high.
  • Great Pay. The average salary of Freshers Masters developers in India is around 6 LPA.
Show More

Key Features

ACTE offers Big Data Masters Program Training in more than 27+ branches with expert trainers. Here are the key features,

  • 40 Hours Course Duration
  • 100% Job Oriented Training
  • Industry Expert Faculties
  • Free Demo Class Available
  • Completed 500+ Batches
  • Certification Guidance

Authorized Partners

ACTE TRAINING INSTITUTE PVT LTD is the unique Authorised Oracle Partner, Authorised Microsoft Partner, Authorised Pearson Vue Exam Center, Authorised PSI Exam Center, Authorised Partner Of AWS and National Institute of Education (nie) Singapore.

Big Data Masters programming Course Content

Syllabus of Core Java Course
Module 1: Introduction to Java
  • Features of Java
  • Simple
  • Secure
  • Portable
  • Robust
  • Multithreading
  • Platform-Independent
  • Distributed.
  • Dynamic
  • New Features of Java 8
  • Introducing Java Environment
  • Java Development Kit
  • Java Platforms
  • Java Virtual Machine
  • Java API
  • Java Programs
  • Installing Java
  • What about CLASSPATH?
  • Java’s Reserve Words
  • Starting a Java program
  • Line 1—public class App
  • Line 2—public static void main(String[] args)
  • Line 3—System.out.println(“Hello from Java!”);
  • Compiling Code 15
  • Compiling Code: Using Command-Line Options
  • Cross-Compilation Options
  • Compiling Code: Checking for Deprecated Methods
  • Running Code
  • Running Code: Using Command-Line Options
  • Commenting Your Code
  • Importing Java Packages and Classes
  • Finding Java Class with CLASSPATH
  • Summary
Module 2: Variables, Arrays and Strings
  • Variables
  • Data Typing
  • Arrays
  • Strings
  • What Data Types are Available?
  • Creating Integer Literals
  • Creating Floating-Point Literals
  • Creating Boolean Literals
  • Creating Character Literals
  • Creating String Literals
  • Creating Binary Literals
  • Using Underscores in Numeric Literals
  • Declaring Integer Variables
  • Declaring Floating-Point Variables
  • Declaring Character Variables
  • Declaring Boolean Variables
  • Initializing Variables Dynamically
  • Conversion between Data Types
  • Automatic Conversions
  • Casting to New Data Types
  • Declaring One-Dimensional
  • Creating One-Dimensional Arrays
  • Initializing One-Dimensional Arrays
  • Declaring Multi-Dimensional Arrays
  • Creating Multi-Dimensional Arrays
  • Initializing Multi-Dimensional Arrays
  • Creating Irregular Multi-Dimensional Arrays
  • Getting an the Length of an Array
  • Understanding General Form of Static Import
  • Importing Static Members
  • The String Class
  • Getting String Length
  • Concatenating Strings
  • Getting Characters and Substrings
  • Searching For and Replacing Strings
  • Changing Case in Strings
  • Checking for Empty String
  • Formatting Numbers in Strings
  • The StringBuffer Class
  • Creating StringBuffers
  • Getting and Setting StringBuffer Lengths and Capacities
  • Setting Characters in String Buffers
  • Appending and Inserting Using StringBuffers
  • Deleting Text in StringBuffers
  • Replacing Text in String Buffer
  • Using the Wrapper Class
  • Autoboxing and Unboxing of Primitive Types
  • Learning the Fundamentals of Varargs Methods
  • Overloading Varargs Methods
  • Learning the Ambiguity in Varargs Methods
  • Using Non-Reifiable Formal Parameters
Module 3: Operators, Conditionals and Loops
  • Operators
  • Conditionals
  • Loops
  • Operator Precedence
  • Incrementing and Decrementing (++ and --)
  • Unary NOT (~ And !)
  • Multiplication and Division (* and /)
  • Modulus (%)
  • Addition and Subtraction (+ and -)
  • Shift Operators (>>, >>>, and <<)
  • Relational Operators (>, >=, <, <=, ==, and !=)
  • Bitwise and Bitwise Logical AND, XOR, and OR (&, ^, and /)
  • Logical (&& and ||)
  • The if-then-else Operator
  • Assignment Operators (= and [operator]=)
  • Using the Math
  • Changes in the Math Class
  • Class StrictMath
  • Comparing Strings
  • The if Statement
  • The else Statement
  • Nested if
  • The if-else Ladders
  • The switch Statement
  • Using Strings in switch Statement
  • The while Loop
  • The do-while Loop
  • The for Loop
  • The for-each Loop
  • Supporting for-each in Your Own Class
  • A (Poor) Solution
  • Significance of for-
  • Nested Loops
  • Using the break Statement
  • Using the continue Statement
  • Using the return Statement
  • Summary
Module 4: Class, Object, Packages and Access Specifiers
  • The Control Overview of a Class
  • Working with Objects
  • Working with Methods
  • Defining Default Methods
  • Working with Constructors
  • Using Default Constructor
  • Using Parameterized Constructors
  • Exploring Packages
  • Studying the Types of Packages
  • Importing Packages
  • Using Access Specifiers
  • Working with Streams API
  • Stream API Overview
  • Collection and Stream
  • Commonly Used Functional Interfaces in Stream
  • Java.util.Optional
  • Aggregate Operations
  • Working with Time API
Module 5: Implementing Object-Oriented Programming in Java
  • Understanding Encapsulation
  • Understanding Abstraction
  • Understanding Inheritance
  • Understanding the final Keyword
  • Preventing Inheritance
  • Declaring Constant
  • Preventing Method Overriding
  • Implementing Interfaces
  • Working with Lambda Expressions
  • Method References
  • Using Lambda Expressions
  • Implementing Abstract Classes and Methods
  • Difference between Abstract Classes and Interfaces
  • Implementing Polymorphism
  • Understanding the Static Polymorphism
  • Understanding the Dynamic Polymorphism
  • Summary
Module 6: Working with Streams, Files and I/O Handling
  • Streams, Readers and Writers
  • Essentials in NIO
  • Buffers
  • Channels
  • Charsets and Selectors
  • Enhancements in NIO with Java 8
  • The Path Interface
  • The Files Class
  • The Paths Class
  • The File Attribute Interfaces
  • The FileSystem Class
  • The FileSystems Class
  • The FileStore Class
  • Prospects of NIO
  • Working with Streams
  • The InputStream Class
  • The OutputStream Class
  • The ByteArrayInputStream Class
  • The ByteArrayOutputStream Class
  • The BufferedInputStream Class
  • The BufferedOutputStream Class
  • The FileInputStream Class
  • The FileOutputStream Class
  • Working with the Reader Class
  • Working with the Writer Class
  • Accepting Input from the Keyboard with the InputStreamReader Class
  • Working with the OutputStreamWriter Class
  • Working with Files
  • Using the File Class
  • Using the FileReader Class
  • Using the FileWriter Class
  • Working with the RandomAccessFile Class
  • Working with Character Arrays
  • Using the CharArrayReader Class
  • Using the CharArrayWriter Class
  • Working with Buffers
  • Using the BufferedReader Class
  • Using the BufferedWriter Class
  • Working with the PushbackReader Class
  • Working with the PrintWriter Class
  • Working with the StreamTokenizer Class
  • Implementing the Serializable Interface
  • Working with the Console Class
  • Working with the Clipboard
  • Working with the Printer
  • Printing with the Formatter Class
  • Using the System.out.printf() Method
  • Using the String.format() Method
  • Formatting Dates Using the String.format() Method
  • Using the Java.util.Formatter Class
  • Scanning Input with the Scanner class
  • Summary
Module 7: Implementing Exception Handling
  • Overview of Exceptions
  • Exception Handling Techniques
  • Rethrowing Catched Exception with Improved Type Checking
  • Built-in Exceptions
  • User-Defined Exceptions
  • Summary
Module 8: Working with Multiple Threads
  • Using Threads in Java
  • Life Cycle of a Thread
  • Synchronization of Threads
  • Multithreaded Custom Class Loader
  • Getting the Main Thread
  • Naming a Thread
  • Pausing a Thread
  • Creating a Thread with the Runnable Interface
  • Creating a Thread with the Thread Class
  • Creating Multiple Threads
  • Joining Threads
  • Checking if a Thread Is Alive
  • Setting Thread Priority and Stopping Threads
  • Synchronizing
  • Communicating between Threads
  • Suspending and Resuming Threads
  • Creating Graphics Animation with Threads
  • Eliminating Flicker in Graphics Animation Created Using Threads
  • Suspending and Resuming Graphics Animation
  • Using Double Buffering
  • Simplifying Producer-Consumer with the Queue Interface
  • Implementing Concurrent Programming
  • Simplifying Servers Using the Concurrency Utilities
  • Knowing Various Concurrency Utilities
  • Learning about the Java.util.concurrent Package
  • Learning about the Java.util.concurrent.locks Package
  • Learning about the Java.util.concurrent.atomic Package
  • Summary
Module 9: Working with Collections Framework
  • The Collection Interfaces
  • The Collection Classes
  • The Map Interfaces
  • The Map Classes
  • Collections Framework Enhancements in Java SE 8
  • Using the Collection Interface
  • The Queue Interface
  • The List Interface
  • The Set Interface
  • The SortedSet Interface
  • Using the Collection Classes
  • Using the Comparator Interface
  • Using the Iterator Interface
  • Using the ListIterator Interface
  • Using the AbstractMap Class
  • Using the HashMap Class
  • Using the TreeMap Class
  • Using the Arrays Class
  • Learning the Fundamentals of Enumerations
  • The Legacy Classes and Interfaces
  • Using the Aggregate Operations
  • Using the Java.util.function Package
  • Summary
Module 10: Creating Packages, Interfaces, JAR Files and Annotations
  • Packages and Interfaces
  • JAR Files
  • The Java API Package
  • The Java.lang Package
  • Basics of Annotation
  • Other Built-In Annotations
  • Creating a Package
  • Creating Packages that have Subpackages
  • Creating an Interface
  • Implementing an Interface
  • Extending an Interface
  • Using Interfaces for Callbacks
  • Performing Operations on a JAR File
  • Marker Annotations
  • Single Member Annotations
  • Summary
Module 11: Working with Java Beans
  • What is Java Bean?
  • Advantages of Java Bean
  • Introspection
  • Persistence
  • Customizers
  • Understanding Java Beans
  • Designing Programs Using Java Beans
  • Creating Applets that Use Java Beans
  • Creating a Java Bean
  • Creating a Bean Manifest File
  • Creating a Bean JAR File
  • Creating a New Bean
  • Adding Controls to Beans
  • Giving a Bean Properties
  • Design Patterns for Properties
  • Using Simple Properties
  • Designing Patterns for Events
  • Learning Methods and Design Patterns
  • Creating Bound Properties
  • Giving a Bean Methods
  • Giving a Bean an Icon
  • Creating a BeanInfo Class
  • Setting Bound and Constrained Properties
  • Implementing Persistence
  • Using the Java Beans API
  • Learning the Basics of an Event
  • Using the Java Beans Conventions
  • Using the Remote Notification and Distributed Notification
  • Using Beans with JSP
  • Summary
Module 12: Networking and Security with Java
  • Basics of Networking
  • Sockets in Java
  • Client-Server Networking
  • Proxy Servers
  • Internet Addressing
  • Domain Name Service
  • Inet4Addresses and Inet6Addresses
  • The URL Class
  • The URI Class
  • URI Syntax and Components
  • TCP/IP and Datagram
  • Blackboard Assignment Retrieval Transaction
  • Understanding Networking Interfaces and Classes in the Java.net Package
  • Understanding the InetAddresses
  • Caching InetAddress
  • Creating and Using Sockets
  • Creating TCP Clients and Servers
  • Understanding the Whois Example
  • Submitting an HTML Form from a Java Program
  • Handling URL
  • Using the URLConnection Objects
  • Working with Datagrams
  • Datagrams Server and Client
  • Working with BART
  • Learning about the Java.security Package
  • Summary
Module 13: Implementing Event Handling and Wrappers in Servlets 3.1
  • Introducing Events
  • Introducing Event Handling
  • Working with the Types of Servlet Events
  • Developing the onlineshop Web Application
  • Introducing Wrappers
  • Working with Wrappers
  • Summary
Module 14: Java Server Pages 2.3 and Expression Language 3.0
  • Introducing JSP Technology
  • Listing Advantages of JSP over Java Servlet
  • Exploring the Architecture of a JSP Page
  • Describing the Life Cycle of a JSP Page
  • Working with JSP Basic Tags and Implicit Objects
  • Working with Action Tags in JSP
  • Exploring EL
  • Using Custom Tag Library with EL Functions
Module 15: Implementing Filters
  • Exploring the Need of Filters
  • Exploring the Working of Filters
  • Exploring Filter API
  • Configuring a Filter
  • Creating a Web Application Using Filters
  • Using Initializing Parameter in Filters
  • Manipulating Responses
  • Discussing Issues in Using Threads with Filters
  • Summary
Module 16: Java EE Design Patterns
  • Describing the Java EE Application Architecture
  • Introducing a Design Pattern
  • Discussing the Role of Design Patterns
  • Exploring Types of Patterns
  • Summary
Module 17: Implementing SOA using Java Web Services
  • Section A: Exploring SOA and Java Web Services
  • Overview of SOA
  • Describing the SOA Environment
  • Overview of JWS
  • Role of WSDL, SOAP and Java/XML Mapping in SOA
  • Section B: Understanding Web Service Specifications to Implement SOA
  • Exploring the JAX-WS 2.2 Specification
  • Exploring the JAXB 2.2 Specification
  • Exploring the WSEE 1.3 Specification
  • Exploring the WS-Metadata 2.2 Specification
  • Describing the SAAJ 1.3 Specification
  • Working with SAAJ and DOM APIs
  • Describing the JAXR Specification
  • JAXR Architecture
  • Exploring the StAX 1.0 Specification
  • Exploring the WebSocket 1.0 Specification
  • Describing the JAX-RS 2.0 Specification
  • Exploring the JASON-P 1.0 Specification
  • Section C: Using the Web Service Specifications
  • Using the JAX-WS 2.2 Specification
  • Using the JAXB 2.2 Specification
  • Using the WSEE and WS-Metadata Specifications
  • Implementing the SAAJ Specification
  • Implementing the JAXR Specification
  • Implementing the StAX Specification
Syllabus of SQL Training Course
Module 1:Introduction of Web & PHP
  • What is PHP?
  • The history of PHP
  • Why choose PHP?
  • Installation overview
Module 2: First Steps
  • Embedding PHP code on a page
  • Outputting dynamic text
  • The operational trail
  • Inserting code comments
Module 3: Exploring Data Types
  • Variables
  • Strings
  • String functions
  • Numbers part one: Integers
  • Numbers part two: Floating points
  • Arrays
  • Associative arrays
  • Array functions
  • Booleans
  • NULL and empty
  • Type juggling and casting
  • Constants
Module 4: Control Structures: Logical Expressions
  • If statements
  • Else and elseif statements
  • Logical operators
  • Switch statements
Module 5: Control Structures: Loops
  • While loops
  • For loops
  • Foreach loops
  • Continue
  • Break
  • Understanding array pointers
Module 6: User-Defined Functions
  • Defining functions
  • Function arguments
  • Returning values from a function
  • Multiple return values
  • Scope and global variables
  • Setting default argument values
Module 7: Debugging
  • Common problems
  • Warnings and errors
  • Debugging and troubleshooting
Module 8: Building Web Pages with PHP
  • Links and URLs
  • Using GET values
  • Encoding GET values
  • Encoding for HTML
  • Including and requiring files
  • Modifying headers
  • Page redirection
  • Output buffering
Module 9: Working with Forms and Form Data
  • Building forms
  • Detecting form submissions
  • Single-page form processing
  • Validating form values
  • Problems with validation logic
  • Displaying validation errors
  • Custom validation functions
  • Single-page form with validations
Module 10: Working with Cookies and Sessions
  • Working with cookies
  • Setting cookie values
  • Reading cookie values
  • Unsetting cookie values
  • Working with sessions
Module 11: MySQL Basics
  • MySQL introduction
  • Creating a database
  • Creating a database table
  • CRUD in MySQL
  • Populating a MySQL database
  • Relational database tables
  • Populating the relational table
Module 12: Using PHP to Access MySQL
  • Database APIs in PHP
  • Connecting to MySQL with PHP
  • Retrieving data from MySQL
  • Working with retrieved data
  • Creating records with PHP
  • Updating and deleting records with PHP
  • SQL injection
  • Escaping strings for MySQL
  • Introducing prepared statements
Module 13: Building a Content Management System (CMS)
  • Blueprinting the application
  • Building the CMS database
  • Establishing your work area
  • Creating and styling the first page
  • Making page assets reusable
  • Connecting the application to the database
Module 14: Using Site Navigation to Choose Content
  • Adding pages to the navigation subjects
  • Refactoring the navigation
  • Selecting pages from the navigation
  • Highlighting the current page
  • Moving the navigation to a function
Module 15: Application CRUD
  • Finding a subject in the database
  • Refactoring the page selection
  • Creating a new subject form
  • Processing form values and adding subjects
  • Passing data in the session
  • Validating form values
  • Creating an edit subject form
  • Using single-page submission
  • Deleting a subject
  • Cleaning up
  • Assignment: Pages CRUD
  • Assignment results: Pages CRUD
Module 16: Building the Public Area
  • The public appearance
  • Using a context for conditional code
  • Adding a default subject behaviour
  • The public content area
  • Protecting page visibility
Module 17: Regulating Page Access
  • User authentication overview
  • Admin CRUD
  • Encrypting passwords
  • Salting passwords
  • Adding password encryption to CMS
  • New PHP password functions
  • Creating a login system
  • Checking for authorization
  • Creating a logout page
Module 18: Advanced PHP Techniques
  • Using variable variables
  • Applying more array functions
  • Building dates and times: Epoch/Unix
  • Formatting dates and times: Strings and SQL
  • Setting server and request variables
  • Establishing global and static variable scope
  • Making a reference assignment
  • Using references as function arguments
  • Using references as function return values
Module 19: Introduction to Object-Oriented Programming (OOP)
  • Introducing the concept and basics of OOP
  • Defining classes
  • Defining class methods
  • Instantiating a class
  • Referencing an instance
  • Defining class properties
<strongModule 20: OOP in Practice
  • Understanding class inheritance
  • Setting access modifiers
  • Using setters and getters
  • Working with the static modifier
  • Reviewing the scope resolution operator
  • Referencing the Parent class
  • Using constructors and destructors
  • Cloning objects
  • Comparing objects
Module 21: Working with Files and Directories
  • File system basics
  • Understanding file permissions
  • Setting file permissions
  • PHP permissions
  • Accessing files
  • Writing to files
  • Deleting files
  • Moving the file pointer
  • Reading files
  • Examining file details
  • Working with directories
  • Viewing directory content
Module 22: Sending Emails
  • Configuring PHP for email
  • Sending email with mail()
  • Using headers
  • Reviewing SMTP
  • Using PHPMailer
Syllabus of Linux Administrator Training Course
Module 1: Automating Programs
  • Run Levels
  • /etc/rc.d Files
  • Customization of Run Levels
  • cron and anacron
  • at and batch
Module 2: Login Options
  • Console Logon
  • Controlling Console Login
  • Virtual Consoles
  • Serial Login
  • Remote Login
  • ssh Login
Module 3: Building a Custom Linux Kernel
  • Kernel Versions
  • Kernel Source Files
  • Kernel Patch Files
  • Kernel Configuration
  • Kernel Building
  • Testing a New Kernel
Module 4: The GNU/Linux Filesystem
  • Partition Types
  • Filesystem Types
  • Mounting
  • Automount
  • File Types
  • File Security
Module 5: Key Filesystem Locations
  • Boot Files
  • User Files
  • Administrator Files
  • Configuration Files
  • Log Files
Module 6: The /proc Pseudo Filesystem
  • Process Info
  • Kernel Config Info
  • Hardware Info
  • Changing /proc Info
  • Sysctl
Module 7: BASH – Borne Again Shell
  • Key /bin Commands
  • Key /sbin Commands
  • History
  • man and info
  • vi
  • Using Shell Scripts
Module 8: User Management
  • Users and Groups
  • Home Directories
  • Password Files
  • PAM
  • Quotas
  • NIS Intro
Module 9: Software Management
  • tar Files
  • Patch Files
  • RPM
Module 10: Hardware Management
  • Types of Devices
  • /dev Namespace
  • Modules
Module 11: Network Management
  • Types of Network Devices
  • Monitoring Network Devices
  • Controlling Network Services
  • xinted
  • iptables
Module 12: Network Services – Part I
  • DHCP
  • DNS
  • SSH
Module 13: Network Services – Part II
  • FTP
  • NFS
  • Samba
Module 14: Network Services – Part III
  • Sendmail
  • Apache
  • Squid Proxy Server
Module 15: The X Window System
  • X Servers and X Clients
  • XFree86
  • X Fonts
  • GTK and KDE
Module 16: Exam Practice
Module 17: Installation Challenges
Module 18: Configuration Challenges
Module 19: Troubleshooting Challenges
Syllabus of Hadoop Course
Module 1: Introduction to Hadoop
  • High Availability
  • Scaling
  • Advantages and Challenges
Module 2: Introduction to Big Data
  • What is Big data
  • Big Data opportunities,Challenges
  • Characteristics of Big data
Module 3: Introduction to Hadoop
  • Hadoop Distributed File System
  • Comparing Hadoop & SQL
  • Industries using Hadoop
  • Data Locality
  • Hadoop Architecture
  • Map Reduce & HDFS
  • Using the Hadoop single node image (Clone)
Module 4: Hadoop Distributed File System (HDFS)
  • HDFS Design & Concepts
  • Blocks, Name nodes and Data nodes
  • HDFS High-Availability and HDFS Federation
  • Hadoop DFS The Command-Line Interface
  • Basic File System Operations
  • Anatomy of File Read,File Write
  • Block Placement Policy and Modes
  • More detailed explanation about Configuration files
  • Metadata, FS image, Edit log, Secondary Name Node and Safe Mode
  • How to add New Data Node dynamically,decommission a Data Node dynamically (Without stopping cluster)
  • FSCK Utility. (Block report)
  • How to override default configuration at system level and Programming level
  • HDFS Federation
  • ZOOKEEPER Leader Election Algorithm
  • Exercise and small use case on HDFS
Module 5: Map Reduce
  • Map Reduce Functional Programming Basics
  • Map and Reduce Basics
  • How Map Reduce Works
  • Anatomy of a Map Reduce Job Run
  • Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
  • Job Completion, Failures
  • Shuffling and Sorting
  • Splits, Record reader, Partition, Types of partitions & Combiner
  • Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots
  • Types of Schedulers and Counters
  • Comparisons between Old and New API at code and Architecture Level
  • Getting the data from RDBMS into HDFS using Custom data types
  • Distributed Cache and Hadoop Streaming (Python, Ruby and R)
  • YARN
  • Sequential Files and Map Files
  • Enabling Compression Codec’s
  • Map side Join with distributed Cache
  • Types of I/O Formats: Multiple outputs, NLINEinputformat
  • Handling small files using CombineFileInputFormat
Module 6: Map Reduce Programming – Java Programming
  • Hands on “Word Count” in Map Reduce in standalone and Pseudo distribution Mode
  • Sorting files using Hadoop Configuration API discussion
  • Emulating “grep” for searching inside a file in Hadoop
  • DBInput Format
  • Job Dependency API discussion
  • Input Format API discussion,Split API discussion
  • Custom Data type creation in Hadoop
Module 7: NOSQL
  • ACID in RDBMS and BASE in NoSQL
  • CAP Theorem and Types of Consistency
  • Types of NoSQL Databases in detail
  • Columnar Databases in Detail (HBASE and CASSANDRA)
  • TTL, Bloom Filters and Compensation
Module 8: HBase
  • HBase Installation, Concepts
  • HBase Data Model and Comparison between RDBMS and NOSQL
  • Master & Region Servers
  • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture
  • Catalog Tables
  • Block Cache and sharding
  • SPLITS
  • DATA Modeling (Sequential, Salted, Promoted and Random Keys)
  • Java API’s and Rest Interface
  • Client Side Buffering and Process 1 million records using Client side Buffering
  • HBase Counters
  • Enabling Replication and HBase RAW Scans
  • HBase Filters
  • Bulk Loading and Co processors (Endpoints and Observers with programs)
  • Real world use case consisting of HDFS,MR and HBASE
Module 9: Hive
  • Hive Installation, Introduction and Architecture
  • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
  • Meta store, Hive QL
  • OLTP vs. OLAP
  • Working with Tables
  • Primitive data types and complex data types
  • Working with Partitions
  • User Defined Functions
  • Hive Bucketed Tables and Sampling
  • External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
  • Dynamic Partition
  • Differences between ORDER BY, DISTRIBUTE BY and SORT BY
  • Bucketing and Sorted Bucketing with Dynamic partition
  • RC File
  • INDEXES and VIEWS
  • MAPSIDE JOINS
  • Compression on hive tables and Migrating Hive tables
  • Dynamic substation of Hive and Different ways of running Hive
  • How to enable Update in HIVE
  • Log Analysis on Hive
  • Access HBASE tables using Hive
  • Hands on Exercises
Module 10: Pig
  • Pig Installation
  • Execution Types
  • Grunt Shell
  • Pig Latin
  • Data Processing
  • Schema on read
  • Primitive data types and complex data types
  • Tuple schema, BAG Schema and MAP Schema
  • Loading and Storing
  • Filtering, Grouping and Joining
  • Debugging commands (Illustrate and Explain)
  • Validations,Type casting in PIG
  • Working with Functions
  • User Defined Functions
  • Types of JOINS in pig and Replicated Join in detail
  • SPLITS and Multiquery execution
  • Error Handling, FLATTEN and ORDER BY
  • Parameter Substitution
  • Nested For Each
  • User Defined Functions, Dynamic Invokers and Macros
  • How to access HBASE using PIG, Load and Write JSON DATA using PIG
  • Piggy Bank
  • Hands on Exercises
Module 11: SQOOP
  • Sqoop Installation
  • Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV, Compressing, Control Parallelism, All tables Import)
  • Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
  • Free Form Query Import
  • Export data to RDBMS,HIVE and HBASE
  • Hands on Exercises
Module 12: HCatalog
  • HCatalog Installation
  • Introduction to HCatalog
  • About Hcatalog with PIG,HIVE and MR
  • Hands on Exercises
Module 13: Flume
  • Flume Installation
  • Introduction to Flume
  • Flume Agents: Sources, Channels and Sinks
  • Log User information using Java program in to HDFS using LOG4J and Avro Source, Tail Source
  • Log User information using Java program in to HBASE using LOG4J and Avro Source, Tail Source
  • Flume Commands
  • Use case of Flume: Flume the data from twitter in to HDFS and HBASE. Do some analysis using HIVE and PIG
Module 14: More Ecosystems
  • HUE.(Hortonworks and Cloudera)
Module 15: Oozie
  • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.,to show how to schedule Sqoop Job, Hive, MR and PIG
  • Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour
  • Zoo Keeper
  • HBASE Integration with HIVE and PIG
  • Phoenix
  • Proof of concept (POC)
Module 16: SPARK
  • Spark Overview
  • Linking with Spark, Initializing Spark
  • Using the Shell
  • Resilient Distributed Datasets (RDDs)
  • Parallelized Collections
  • External Datasets
  • RDD Operations
  • Basics, Passing Functions to Spark
  • Working with Key-Value Pairs
  • Transformations
  • Actions
  • RDD Persistence
  • Which Storage Level to Choose?
  • Removing Data
  • Shared Variables
  • Broadcast Variables
  • Accumulators
  • Deploying to a Cluster
  • Unit Testing
  • Migrating from pre-1.0 Versions of Spark
  • Where to Go from Here
Syllabus of Apache Spark with Scala Course

Module 1: Introduction

  • 1. Overview of Hadoop 
  • 2. Architecture of  HDFS  & YARN
  • 3. Overview of Spark version 2.2.0
  • 4. Spark Architecture
  • 5. Spark  Components 
  • 6. Comparison of  Spark &  Hadoop
  • 7. Installation of Spark v 2.2.0 on Linux 64 bit

Module 2: Spark Core

  • 1. Exploring the Spark shell 
  • 2. Creating Spark Context
  • 3. Operations on Resilient Distributed Dataset – RDD
  • 4. Transformations & Actions 
  • 5. Loading Data and Saving Data

Module 3: Spark SQL & Hive SQL

  • 1. Introduction to SQL  Operations
  • 2. SQL Context
  • 3. Data Frame
  • 4. Working with Hive
  • 5. Loading Partitioned Tables
  • 6. Processing  CSV, Json ,Parquet files

Module 4: Scala Programming

  • 1. Introduction to Scala
  • 2. Feature of Scala
  • 3. Scala vs Java Comparison
  • 4. Data types
  • 5. Data Structure
  • 6. Arrays
  • 7. Literals
  • 8. Logical Operators
  • 9. Mutable & Immutable variables
  • 10. Type interface

Module 5: Scala Functions

  • 1. Oops  vs Functions
  • 2. Anonymous 
  • 3. Recursive 
  • 4. Call-by-name
  • 5. Currying
  • 6. Conditional statement

Module 6: Scala Collections

  • 1. List
  • 2. Map
  • 3. Sets
  • 4. Options
  • 5. Tuples
  • 6. Mutable collection
  • 7. Immutable collection
  • 8. Iterating
  • 9. Filtering and counting 
  • 10. Group By
  • 11. Flat Map
  • 12. Word count
  • 13. File Access

Module 7: Scala Object Oriented Programming

  • 1. Classes ,Objects & Properties
  • 2. Inheritance

Module 8: Spark Submit

  • 1. Maven  build tool implementation
  • 2. Build Libraries
  • 3. Create  Jar files 
  • 4. Spark-Submit

Module 9: Spark Streaming

  • 1. Overview  of Spark Streaming
  • 2. Architecture of Spark Streaming 
  • 3. File streaming
  • 4. Twitter Streaming

Module 10: Kafka Streaming

  • 1. Overview  of Kafka Streaming
  • 2. Architecture of Kafka Streaming 
  • 3. Kafka Installation
  • 4. Topic
  • 5. Producer
  • 6. Consumer
  • 7. File streaming
  • 8. Twitter Streaming

Module 11: Spark Mlib

  • 1. Overview  of Machine Learning Algorithm
  • 2. Linear Regression
  • 3. Logistic Regression

Module 12: Spark GraphX

  • 1. GraphX overview
  • 2. Vertices
  • 3. Edges
  • 4. Triplets
  • 5. Page Rank
  • 6. Pregel

Module 13: Performance Tuning

  • 1. On-Off-heap memory tuning
  • 2. Kryo Serialization
  • 3. Broadcast Variable
  • 4. Accumulator Variable
  • 5. DAG Scheduler
  • 6. Data Locality
  • 7. Check Pointing
  • 8. Speculative Execution
  • 9. Garbage Collection

Module 14: Project Planning, Monitoring Trouble Shooting

  • 1. Master – Driver Node capacity
  • 2. Slave –   Worker Node capacity
  • 3. Executor capacity
  • 4. Executor core capacity
  • 5. Project scenario and execution
  • 6. Out-of-memory error handling
  • 7. Master logs, Worker logs, Driver  logs
  • 8. Monitoring Web UI 
  • 9. Heap memory dump
Show More
Show Less
Need customized curriculum?

Hands-on Real Time Projects in Big Data Concepts

Project 1
Cloud Hosting Using Big Data

It leads to host the data on on-site server and Java-based framework used to manipulate data stored in the cloud.

Project 2
Document Analysis Application

Hadoop tools integrate the infrastructure for document analysis with distance metric rank text search operations in documents.

Project 3
Trend Analysis of Weblogs

It presenting users activity trends based on browsing sessions, most visited web pages, trending keywords.

Project 4
Predicting Flight Delays

Using the Spark to perform practical statistical analysis (descriptive) over an airline dataset.

Our Top Hiring Partner for Placements

ACTE offers placement opportunities as add-on to every student / professional who completed our classroom or online training. Some of our students are working in these companies listed below.

  • We are associated with top organizations like HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc. It make us capable to place our students in top MNCs across the globe
  • We have separate student’s portals for placement, here you will get all the interview schedules and we notify you through Emails.
  • After completion of 70% Big Data Masters Program training course content, we will arrange the interview calls to students & prepare them to F2F interaction
  • Big Data Masters Program Trainers assist students in developing their resume matching the current industry needs
  • We have a dedicated Placement support team wing that assist students in securing placement according to their requirements
  • We will schedule Mock Exams and Mock Interviews to find out the GAP in Candidate Knowledge

Be a Certified Expert in Big Data Masters Program

Acte Certification is Accredited by all major Global Companies around the world. We provide after completion of the theoretical and practical sessions to fresher's as well as corporate trainees.

Our certification at Acte is accredited worldwide. It increases the value of your resume and you can attain leading job posts with the help of this certification in leading MNC's of the world. The certification is only provided after successful completion of our training and practical based projects.

Complete Your Course

a downloadable Certificate in PDF format, immediately available to you when you complete your Course

Get Certified

a physical version of your officially branded and security-marked Certificate.

Get Certified

About Experienced Big Data Master Programming Trainer

  • Big Data Masters Program Training Course:Trainers are certified professionals with 7+ years of experience in their respective domain as well as they are currently working with Top MNCs.
  • As all Trainers are Big data domain working professionals so they are having many live projects, trainers will use these projects during training sessions.
  • All our Trainers are working with companies such as Cognizant, Dell, Infosys, IBM, L&T InfoTech, TCS, HCL Technologies, etc.
  • Trainers are also help candidates to get placed in their respective company by Employee Referral / Internal Hiring process.
  • Our trainers are industry-experts and subject specialists who have mastered on running applications providing Best Big Data Masters Program training to the students.
  • We have received various prestigious awards for Big Data Masters Program Training recognized IT organizations.

Java Course Reviews

Our ACTE Reviews are listed here. Reviews of our students who completed their training with us and left their reviews in public portals and our primary website of ACTE & Video Reviews.

NANCY RAMKUMAR

Studying

I had completed my java with advance in by ACTE. The best place to excel your next phase of career. The trainers and faculty here were very friendly and comfortable. My trainer had explained each and every topics clearly and he won't move to the another topic until I was clear in it. Thanks to my trainer and ACTE for this wonderful opportunity!!

CHANDRAN KANNAN

Software Engineer

It is a great curse for beginners and for filling in some gaps for intermediate programmers. I wouldn't recommend it though for advanced programmers as the knowledge is rather basic and even at x2.0 speed it will become boring. Again, great course overall of beginners who want to get started with Java. Thanks!

AMAN ADITHYA

Software Engineer

This course is really great, it's very awesome that the course constantly get updated and you get answers in Q&A very fast, also instructor explanation is very good and clear, this is the only course you need to master Java and Mr.Venket does a really good job on that, the only con for me was that it didn't have much theory covered it went right to code without showing slides about how it works, but thankfully they are adding them now, so this is really a 5 star course, thank you ACTE for these amazing courses.

KEERTHANA V

Studying

One of the best Programming courses that i have taken in a long time , ACTE has put lot of effort into making the course easy to learn , even for a Java Novice like me, which makes it truly a masterclass course to attend ,and the responses from Goran and others have been very helpful .

RAMYA PANDIAN

Software Testing

This Course is really a masterclass, covers from basic to advanced level. Would definitely recommend it to anyone interested in learning Big Data Masters Program. All concepts explained in a well-structured course. Tim teaches the concepts really well with coding examples. Follow along with him on code, you will learn a lot on writing a professional code too!.. Thanks, ACTE & Team

View More Reviews
Show Less

Big Data Masters Program & Placement Course FAQs

Looking for better Discount Price?

Call now: +9193833 99991 and know the exciting offers available for you!
  • ACTE is the Legend in offering placement to the students. Please visit our Placed Students List on our website
  • We have strong relationship with over 700+ Top MNCs like SAP, Oracle, Amazon, HCL, Wipro, Dell, Accenture, Google, CTS, TCS, IBM etc.
  • More than 3500+ students placed in last year in India & Globally
  • ACTE conducts development sessions including mock interviews, presentation skills to prepare students to face a challenging interview situation with ease.
  • 85% percent placement record
  • Our Placement Cell support you till you get placed in better MNC
  • Please Visit Your Student Portal | Here FREE Lifetime Online Student Portal help you to access the Job Openings, Study Materials, Videos, Recorded Section & Top MNC interview Questions
    ACTE Gives Certificate For Completing A Course
  • Certification is Accredited by all major Global Companies
  • ACTE is the unique Authorized Oracle Partner, Authorized Microsoft Partner, Authorized Pearson Vue Exam Center, Authorized PSI Exam Center, Authorized Partner Of AWS and National Institute of Education (NIE) Singapore
  • The entire Big Data Masters Program & Placement training has been built around Real Time Implementation
  • You Get Hands-on Experience with Industry Projects, Hackathons & lab sessions which will help you to Build your Project Portfolio
  • GitHub repository and Showcase to Recruiters in Interviews & Get Placed
All the instructors at ACTE are practitioners from the Industry with minimum 9-12 yrs of relevant IT experience. They are subject matter experts and are trained by ACTE for providing an awesome learning experience.
No worries. ACTE assure that no one misses single lectures topics. We will reschedule the classes as per your convenience within the stipulated course duration with all such possibilities. If required you can even attend that topic with any other batches.
We offer this course in “Class Room, One to One Training, Fast Track, Customized Training & Online Training” mode. Through this way you won’t mess anything in your real-life schedule.

Why Should I Learn Big Data Masters Program & Placement Course At ACTE?

  • Big Data Masters Program & Placement Course in ACTE is designed & conducted by Big Data Masters Program & Placement experts with 10+ years of experience in the Big Data Masters Program & Placement domain
  • Only institution in India with the right blend of theory & practical sessions
  • In-depth Course coverage for 60+ Hours
  • More than 50,000+ students trust ACTE
  • Affordable fees keeping students and IT working professionals in mind
  • Course timings designed to suit working professionals and students
  • Interview tips and training
  • Resume building support
  • Real-time projects and case studies
Yes We Provide Lifetime Access for Student’s Portal Study Materials, Videos & Top MNC Interview Question.
You will receive ACTE globally recognized course completion certification Along with National Institute of Education (NIE), Singapore.
We have been in the training field for close to a decade now. We set up our operations in the year 2009 by a group of IT veterans to offer world class IT training & we have trained over 50,000+ aspirants to well-employed IT professionals in various IT companies.
We at ACTE believe in giving individual attention to students so that they will be in a position to clarify all the doubts that arise in complex and difficult topics. Therefore, we restrict the size of each Big Data Masters Program & Placement batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Big Data Masters Program & Placement. The course is made up of theoretical classes that teach the basics of each module followed by high-intensity practical sessions reflecting the current challenges and needs of the industry that will demand the students’ time and commitment.
You can contact our support number at 93833 99991 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
Show More
Request for Class Room & Online Training Quotation

Related Category Courses

Related Post
Data Science Masters Program Training Course

Beginner & Advanced level Classes. Hands-On Learning in Data Science Read more

Digital Project Manager Masters Program Training Course

Beginner & Advanced level Classes. Hands-On Learning in DevOps Technologies. Read more

Full Stack Web Developer – MEAN Stack Master Program

Beginner & Advanced level Classes. Hands-On Learning in Web Technologies. Read more

Python Master Program Training Course

Beginner & Advanced level Classes. Hands-On Learning in Python. Best Read more

Software Testing Master Program Training course

Beginner & Advanced level Classes. Hands-On Learning in Software Testing Read more

Data Analyst Masters Program Training Course

Beginner & Advanced level Classes. Hands-On Learning in Data Analyst Read more

Business Analyst Masters Program Training course

Beginner & Advanced level Classes. Hands-On Learning in Concepts of Read more

Automation Testing Masters Program Training Course

Beginner & Advanced level Classes. Hands-On Learning in Fundamentals of Read more

Full Stack Developer Masters Program Training Course

Beginner & Advanced level Classes. Hands-On Learning in Web Technologies. Read more