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Big Data and Hadoop Training in Indira Nagar

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Learn from Certified Experts

  • Beginner & Advanced level Classes.
  • Hands-On Learning in Hadoop.
  • Best Practice for interview Preparation Techniques in Hadoop.
  • Lifetime Access for Student’s Portal, Study Materials, Videos & Top MNC Interview Question.
  • Affordable Fees with Best curriculum Designed by Industrial Hadoop Expert.
  • Delivered by 9+ years of Hadoop Certified Expert | 12402+ Students Trained & 350+ Recruiting Clients.
  • Next Hadoop Batch to Begin this week – Enroll Your Name Now!

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INR18000

INR 14000

Price

INR 20000

INR 16000

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Upcoming Batches

27-May-2024
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

22-May-2024
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

25-May-2024
Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

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

25-May-2024
Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

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

Hear it from our Graduate

Have Cracked Their Dream Job in Top MNC Companies

Learn From Experts, Practice On Projects & Get Placed in IT Company

  • 100% Guaranteed Placement Support for Freshers & Working Professionals
  • You will not only gain knowledge of Hadoop Certification and advanced concepts, but also gain exposure to Industry best practices
  • Experienced Trainers and Lab Facility
  • Hadoop Professional Certification Guidance Support with Exam Dumps
  • Practical oriented / Job oriented Training. Practice on Real Time project scenarios.
  • We have designed an in-depth course so meet job requirements and criteria
  • Resume & Interviews Preparation Support
  • Concepts: High Availability, Big Data opportunities, Challenges, Hadoop Distributed File System (HDFS), Map Reduce, API discussion, Hive, Hive Services, Hive Shell, Hive Server and Hive Web Interface, SQOOP, H Catalogue, Flume, Oozie.
  • START YOUR CAREER WITH HANDOOP CERTIFICATION COURSE THAT GETS YOU A JOB OF UPTO 5 TO 12 LACS IN JUST 60 DAYS!
  • Classroom Batch Training
  • One To One Training
  • Online Training
  • Customized Training
  • Enroll Now

About Hadoop Training Course in Indira Nagar

To get a full understanding of the power of hadoop, you need to actually work with hadoop. Here in ACTE you will get a crash course in how output is sorted, and how to control input keys in such a way that output is sorted according to values. you will learn to understand the complex logic behind hadoop and how to use it effectively. Start Learning with us ACTE Hadoop Classroom & Online Training Course.

Top Job Offered Hadoop Tools Covered
  • Big Data, HDFS

    YARN, Spark

    MapReduce

  • PIG, HIVE

    HBase

    Mahout, Spark MLLib

  • Solar, Lucene

    Zookeeper

    Oozie

Hadoop skills are in demand – this is an undeniable fact! Hence, there is an urgent need for IT professionals to keep themselves in trend with Hadoop and Big Data technologies. Apache Hadoop provides you with means to ramp up your career and gives you the following advantages: Accelerated career growth.

Hadoop is the supermodel of Big Data. If you are a Fresher there is a huge scope if you are skilled in Hadoop. The need for analytics professionals and Big Data architects is also increasing . Today many people are looking to pursue their big data career by grabbing big data jobs as freshers.

Even as a fresher, you can get a job in Hadoop domain. It is definitely not impossible for anyone to land a job in the Hadoop domain if they invest their mind in preparing and putting their best effort in learning and understanding the Hadoop concepts.

We are happy and proud to say that we have strong relationship with over 700+ small, mid-sized and MNCs. Many of these companies have openings for Hadoop. 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.

A Hadoop Cluster uses Master-Slave architecture. It consist of a Single Master (NameNode) and a Cluster of Slaves (DataNodes) to store and process data. Hadoop is designed to run on a large number of machines that do not share any memory or disks. These DataNodes are configured as Cluster using Hadoop Configuration files. Hadoop uses a concept of replication to ensure that at least one copy of data is available in the cluster all the time. Because there are multiple copy of data, data stored on a server that goes offline or dies can be automatically replicated from a known good copy.

  • To learn Hadoop and build an excellent career in Hadoop, having basic knowledge of Linux and knowing the basic programming principles of Java is a must. Thus, to incredibly excel in the entrenched technology of Apache Hadoop, it is recommended that you at least learn Java basics.
  • Learning Hadoop is not an easy task but it becomes hassle-free if students know about the hurdles overpowering it. One of the most frequently asked questions by prospective Hadoopers is- “How much java is required for hadoop”? Hadoop is an open source software built on Java thus making it necessary for every Hadooper to be well-versed with at least java essentials for hadoop. Having knowledge of advanced Java concepts for hadoop is a plus but definitely not compulsory to learn hadoop. Your search for the question “How much Java is required for Hadoop?” ends here as this article explains elaborately on java essentials for Hadoop.

Apache Hadoop is an open source platform built on two technologies Linux operating system and Java programming language. Java is used for storing, analysing and processing large data sets. ... Hadoop is Java-based, so it typically requires professionals to learn Java for Hadoop.

Yes, you can learn Hadoop, without any basic programming knowledge . The only one thing matters is your dedication towards your work. If you really want to learn something, then you can easily learn. It also depends upon on which profile you want to start your work like there are various fields in Hadoop.

Our course ware is designed to give a hands-on approach to the students in Hadoop. 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.

Yes It is worth , Future will be bright. Learning Hadoop will definitely give you a basic understanding about working of other options as well. Moreover, several organizations are using Hadoop for their workload. So there are lot of opportunities for good developers in this domain. Indeed it is!

No Learning Hadoop is not very difficult. Hadoop is a framework of java. Java is not a compulsory prerequisite for learning hadoop. ... Hadoop is an open source software platform for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware.

Hadoop framework can be coded in any language, but still, Java is preferred. For Hadoop, the knowledge of Core Java is sufficient, and it will take approximately 5-9 months. Learning Linux operating system: - It is recommended to have a basic understanding and working of the Linux operating system.

Top reasons to consider a career in Hadoop?

Hadoop brings in better career opportunities in 2015.

Learn Hadoop to pace up with the exponentially growing Big Data Market.

Increased Number of Hadoop Jobs.

Learn Hadoop to pace up with the increased adoption of Hadoop by Big data companies.


5 reasons why Business Intelligence Professionals Should Learn Hadoop

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. 

Hadoop is a being recognized as a vital constituent of BI

  • Industry studies reveal that Hadoop products like MapReduce, Java, Pig, HDFS, Hbase and Hive have gained a strong Other products like Mahout, Zookeeper and Hcatalog would be getting on real shortly.
  • Professionals who have learnt Hadoop have now started integrating Hadoop with DW's, analytic tools, web servers, data visualization tools, reporting tools and analytic databases. Big organizations across the world are witnessing a spurt in their data volumes and this is a chain reaction that is unstoppable.
  • Under such circumstances, slower analysis results in delaying the processing of the data. Hadoop is fast catching up as it allows rapid data crunching through a cluster of nodes.
  • Although, the percentage of organizations that have implemented Hadoop technology is not over 10% as on date, but within the next 4 years this will cross the 51% mark, for sure. In short, the Hadoop trend is will be impacting at least half of the BI/DW segment of the IT sector and this makes it necessary for BI professionals to learn Hadoop.
  • A survey conducted by TWDI, considered as a premier source for Business Intelligence, suggests that almost 78% of users consider Hadoop as a major value addition. The survey volunteers accepted that Hadoop is beneficial when it comes of Big Data analytics.

Hadoop has a cutting edge over traditional RDBMS

One of the toughest parts of BI process is storage of Big Data, handling unstructured data and advanced analytics. BI professionals use various tools to draw useful data that are used to generate customized reports and this is where the  Hadoop File Distribution System (HDFS) proves itself.

The HDFS is designed to allow storing and managing of all data types. The specific advantages of Hadoop over traditional RDBMS are-

  • Hadoop is scalable: Hadoop is highly scalable and is designed to store and distribute huge data through multiple servers operating in parallel. Contrary to traditional RDBMS's that are un-scalable, Hadoop applications can run on thousands of nodes, thus allowing the processing of thousands of terabytes of data at lightning speeds. So the day that BI professionals would be staring at many Hadoop loaded nodes is not far and this makes it essential for them to learn Hadoop.
  • Hadoop is inexpensiveWhen it comes to data explosion, Hadoop has established itself as the most inexpensive storage solution. When it comes to processing massive amounts of data, scaling of traditional RDBMS's proves extremely expensive.
  • Hadoop is Flexible: Be it social media, clickstream data or email conversations, Hadoop has the ability to derive useful data from all types of data resources. Further, Hadoop can be efficiently used for recommendation systems, marketing campaign analysis, fraud detection and data warehousing as well.
  • Hadoop is fail proof: When using Hadoop, data sent to an individual node also replicates on all the other nodes in the cluster, so in case of failure on one node, there is always a backup copy of the data available in the cluster.

Hadoop is good for data integration and BI

  • Relational databases are dominant at present and they integrate well with other information systems. The present day RDBMS are perfect for querying structured data and people are well acquainted with their technicalities. One good thing about Hadoop is that it can work in parallel as well as in conjunction with rational databases. What's more? Storing of archived data on Hadoop is inexpensive and data can be drawn out from the relational database at regular intervals and restore it back in the DB whenever needed.
  • Apache sqoop is a wonderful tool that integrates Hadoop with databases like PostgreSQL, MySQL or Oracle through JDBC which is the regular API to connect databases with Java. Sqoop runs a query on the relational databases and exports the resultant rows in one of the file formats like Binary, Text, Sequence files or Avro. These files can be saved on Hadoop HDFS. Conversely, Sqoop also allows importing formatted file again into the relational database.
  • Once the data is analyzed, Hadoop integrates with a plethora of BI tools like  Tableau, Pentaho, Datameer, BIRT to create interactive dashboards and diagrams for data visualizations.These BI tools connect with Hadoop to present the data in an accessible and to easy to comprehend manner, which facilitates informed consumer and business decisions. 
  • "It's common that Hadoop is used in conjunction with databases. In the Hadoop world, databases don't go away. They just play a different role than Hadoop does," says Charles Zedlewski, VP of product at Cloudera.
  • These advantages of integrating Hadoop with traditional databases will keep motivating businesses to do so. As such, Business Intelligence professionals working with traditional databases will be required to learn Hadoop.

Hadoop is cost effective

  • Handling extraordinary data volumes with traditional technologies is particularly challenging from a technological point of view and it proves extremely expensive, as well. The traditional technologies demand vertical scalability that in-turn demands powerful hardware. Contrary to this, Hadoop offers horizontal scalability that allows using cost effective hardware and scalability, of course, is the nerve center of Big Data projects.
  • Hadoop is 10 times better in terms of scalability over the next available option. A Cloudera Executive assertsHadoop systems, including hardware and software, cost about $1,000 a terabyte or as little as one-twentieth the cost of other data management technologies.
  • This implies that more and more businesses across the world would not be using Hadoop because they Want to, but will adopt Hadoop technologies in the near future because the Have to. This situation in turn suggests that BI professionals have to learn Hadoop.

Great job opportunities for Hadoop Certified BI professionals

  • Learning Hadoop is synonymous with a flourishing career in BI. Hadoop has proven its usefulness in various segments of business. Today, the manufacturing sector uses Hadoop for assessment of product quality. The telecommunication Industry uses Hadoop for content conciliation. Various government organizations use Hadoop for security, Geo-spatial data, search as well as location based push of data.
  • A portal that is considered to be a leader in Big Data Insights reveals that there is an acute shortage of Hadoop skilled professionals. Almost 70% of participants that volunteered for the survey agreed that the data analysts in their respective segments lacked the technical expertise to analyze data on Hadoop.
  • Companies like Amazon,  IBM, MapR, Cloudera and Hortonworks are propelling Hadoop technology to the next frontier. The global market for Hadoop based technologies will be reaching $8.74 billion by 2016 and it is growing at a rapid pace of over 55%. No doubt, this is one of the most important reasons for BI professionals to learn Hadoop!
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Key Features

ACTE Indira Nagar offers Hadoop 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.

 

Curriculum

Syllabus of Hadoop Course in Indira Nagar
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
<strongclass="streight-line-text"> 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
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Need customized curriculum?

Hands-on Real Time Hadoop Projects

Project 1
Customer churn analysis –Telecom Industry

The project involves tracking consumer complaints registered on various Platforms.

Project 2
UBER Projects

Determine dynamic pricing based on traffic congestion, Spark Streaming and Cassandra.

Our Top Hiring Partner for Placements

ACTE Indira Nagar 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% Hadoop training course content, we will arrange the interview calls to students & prepare them to F2F interaction
  • Hadoop 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

Get Certified By MapR Certified Hadoop Developer (MCHD) & Industry Recognized ACTE Certificate

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 Hadoop Trainer

  • Our Hadoop Training in Indira Nagar. 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 Hadoop 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 Hadoop training to the students.
  • We have received various prestigious awards for Hadoop Training in Indira Nagar from recognized IT organizations.

Hadoop Course FAQs

Looking for better Discount Price?

Call now: +91 93833 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 Hadoop 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 Hadoop Course At ACTE?

  • Hadoop Course in ACTE is designed & conducted by Hadoop experts with 10+ years of experience in the Hadoop 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 Hadoop batch to 5 or 6 members
Our courseware is designed to give a hands-on approach to the students in Hadoop. 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 +91 93800 99996 / Directly can do by ACTE.in's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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Request for Class Room & Online Training Quotation

      Job Opportunities in Big Data

      More than 35% of Data Professionals Prefer Big Data. Big Data Is Widely Recognized as the Most Popular and In-demand Data Technology in the Tech World.

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