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Big Data and Hadoop Training in Tiruchirappalli

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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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Upcoming Batches

22-Apr-2024
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

17-Apr-2024
Mon-Fri

Weekdays Regular

08:00 AM & 10:00 AM Batches

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

20-Apr-2024
Sat,Sun

Weekend Regular

(10:00 AM - 01:30 PM)

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

20-Apr-2024
Sat,Sun

Weekend Fasttrack

(09:00 AM - 02:00 PM)

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

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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

This is How ACTE Students Prepare for Better Jobs

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About Hadoop Training Course in Tiruchirappalli

ACTE offers a training course in Big Data and Hadoop. This course will equip you with a good level of knowledge in Big Data and Hadoop. Start building your own practical experience and learn useful skills for your personal growth with ACTE. The entire training course content is in line with these certifications programs and helps you clear these certification exams with ease. 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.


Make a Career Change from Mainframe to Hadoop - Learn Why

Mainframe legacy systems might not be a part of technology conversations anymore but they are of critical importance to a business. The largest and critical industries across the globe - healthcare, insurance, finance and retail, still generate data from Mainframes. Mainframe data cannot be ignored because it drives mission critical applications across myriad industries. Can any distributed platform address mainframe workload?  Is there an easy and cost effective way to make use of it? The answer is definitely a resounding YES.

Using Hadoop distributed processing framework to offload data from the legacy Mainframe systems, companies can optimize the cost involved in maintaining Mainframe CPUs. As increasing number of organizations are involved in Mainframe to Hadoop migration, to exploit big data – let’s take a look at what are the top skills, technicalities required and cost challenges involved, in migrating from Mainframe to Hadoop.

Need to Offload Data from Mainframes to Hadoop

  • Organizations run critical applications on Mainframe systems, which generate huge volumes of data but lack the capability to support novel business requirements of processing unstructured data and also involve huge maintenance costs.
  • The wealth of the data stored and processed in mainframes is vital but the resources required to manage data on mainframe systems are highly expensive. Businesses today, spend approximately $100,000 per TB, every year, to lock their data and back it up to tape. However, to manage the same amount of data on Hadoop –it costs $1000 to $4000.
  • To address this huge cost of operation, organizations are increasingly offloading data to the Hadoop framework by shifting to clusters of commodity servers to analyse the bulk of their data. Offloading data to Hadoop might not be important but has potential benefits to the business, as the data is available to the analysts to explore and discern novel business opportunities, ensuring that no information is left untapped.

Challenges to be Successful with Hadoop and Mainframes

  • Mainframe systems contain highly sensitive information whereas Hadoop manages data from diverse sources from harmless tweets to sensitive information. This implies that any data transfers from mainframes to Hadoop must be performed with utmost care, to ensure security. Organizations need to ensure that any software they install on mainframe systems to load data into Hadoop should be legitimate and have a good security track record.
  • Many people think that moving mainframe data to Hadoop is very simple. However, this is not true, as there are several integration gaps, since Hadoop does not have any native support for mainframes.
  • Mainframes and Hadoop both use different data formats - Hadoop uses ASCII format whereas Mainframes use packed decimal EBCDIC format.
  • There is a huge skills gap, as both mainframe and Hadoop skills are in-demand. If finding a JCL or COBOL developer is difficult then finding a Hadoop developer who also understands mainframes is like trying to find a needle in haystack.
  • Mainframe data has to be rationalized with COBOL copybook, which requires a special skillset that a person with only Hadoop skill might not possess and vice-versa. The switch from Mainframes to Hadoop is achievable and is a great technological adventure.
  • There are many solutions from vendors like Syncsort, Veristorm, Compuware and BMC that target mainframe data with enhanced Hadoop ETL tools. Veristorm and Syncsort are developing various solutions to clear the bottleneck for organizations that still have valuable information locked in mainframe systems.

With the advent of scalable fault tolerant and cost effective big data technology like Hadoop, organizations can now easily reduce maintenance and processing expenses involved with mainframe legacy systems by including a Hadoop layer or by off-loading the batch processing data from Mainframes to Hadoop.

Hadoop fits well among COBOL and other legacy technologies, so, by migrating or offloading from mainframe to Hadoop, batch processing can be done at a lower cost, and in a fast and efficient manner. Moving from mainframe to Hadoop is a good move now, because of the reduced batch processing and infrastructure costs. Also, Hadoop code is flexible and easily maintainable, which helps in rapid development of new functionalities.

Organizations should begin with creating copies of selected mainframe datasets in HDFS and then migrating huge volumes of data from various semi-structured sources and RDBMs. The ultimate step is to migrate expensive batch mainframe workloads to Hadoop.

There are several Hadoop components that organizations can take direct advantage of, when offloading from Mainframes to Hadoop-

  • HDFS, Hive and MapReduce components of the Hadoop framework help process huge legacy data, batch workloads and store the intermediate results of processing. Batch jobs can be taken off from mainframe systems, processed using Pig, Hive or MapReduce and the result can be moved back to mainframe systems which helps reduce MIPS (million instructions per second) cost.
  • Sqoop and Flume components of the Hadoop framework helps move data between Hadoop and RDBMS.
  • Oozie, component of the Hadoop framework, helps schedule batch jobs just like the job scheduler in mainframes.

Advantages of Using Hadoop with Mainframes for Legacy Workload

  • Organizations can retain and analyse data at much granular level with longer history.
  • Hadoop reduces the cost and strain on legacy platforms.
  • Hadoop helps revolutionize enterprise workloads by reducing batch processing times for mainframes and EDW.

Why Mainframe Professionals should learn Hadoop ?

Huge Talent Crunch for “Mainframe + Hadoop” Professionals

  • The lack of talent for “Mainframe+ Hadoop” skills, is becoming a persistent problem for the CIOs of any organization that want to push mainframe-hosted data and Hadoop-powered analysis closer together. Companies that still depend on mainframes are finding it difficult to hire professionals who possess mainframe knowledge along with Hadoop skills to support transaction processing, legacy applications and have the capability to leverage analytics from the data.
  • The future is all set for Apache Hadoop and mainframes to rule the world of data managing systems. Organizations that are migrating from mainframes to Hadoop, are in search of professionals with knowledge of analytics. This is the best time for mainframe professionals to start updating their skillset with Hadoop.
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Key Features

ACTE Tiruchirappalli 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 Tiruchirappalli
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 Tiruchirappalli 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 Tiruchirappalli. 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 Tiruchirappalli from recognized IT organizations.

Hadoop Course Reviews

Our ACTE Tiruchirappalli 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.

Mahalakshmi

Studying

"I would like to recommend to the learners who wants to be an expert on Big Data just one place i.e.,ACTE institute at Anna nagar. After several research with several Training Institutes I ended up with ACTE. My Big Data Hadoop trainer was so helpful in replying, solving the issues and Explanations are clean, clear, easy to understand the concepts and it is one of the Best Training Institute for Hadoop Training"

Rakesh

Software Engineer

I have completed the course of Hadoop from ACTE in Tiruchirappalli and I must say that they are really capable of kicking-in the interest on subject as the faculty holds your hands throughout the course and gives you a practical experience with real case scenarios for better understanding. They offer flexible timing's and most Importantly they are in-line with all the new social trends which will be imparted to us as well.

Harish

Software Engineer

The training here is very well structured and is very much peculiar with the current industry standards. Working on real-time projects & case studies will help us build hands-on experience which we can avail at this institute. Also, the faculty here helps to build knowledge of interview questions & conducts repetitive mock interviews which will help in building immense confidence. Overall it was a very good experience in availing training in Tambaram at the ACTE Institute. I strongly recommend this institute to others for excelling in their career profession.

Sindhuja

Studying

I had an outstanding experience in learning Hadoop from ACTE Institute. The trainer here was very much focused on enhancing knowledge of both theoretical & as well as practical concepts among the students. They had also focused on mock interviews & test assignments which helped me towards boosting my confidence.

Kaviya

Software Engineer

The Hadoop Training by sundhar sir Velachery branch was great. The course was detailed and covered all the required knowledge essential for Big Data Hadoop. The time mentioned was strictly met and without missing any milestone.Should be recommended who is looking Hadoop training course ACTE institute in Chennai.

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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

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