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Hadoop Training in Indore

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30-Nov -2022

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03- Dec - 2022

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  • Detailed knowledge of Big Data, including HDFS, YARN (Another Resource Negotiator), and MapReduce, including the distributed file system.
  • Complete knowledge of various tools such as pig, hive, qoop, flume, oozie, and HBase in Hadoop Ecosystem.
  • The ability in HDFS to input data using Sqoop & Flume and analyze the large HDFS data sets.
  • The exposure to many projects based on the real industry in the CloudLab.
  • Various projects covering different data sets from various fields like banking, telecommunications, social media, insurance, and e-commerce.
  • A Hadoop expert is intensively involved during the Big Data Hadoop training to learn industry standards and best practices
  • 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.
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Course Objectives

Big Data is the quickest developing and most encouraging innovation for the treatment of a lot of information. This Big Data Hadoop preparation assists you with accomplishing the most elevated expert capabilities. Essentially every top MNC attempts to enter Big Data Hadoop, which makes it fundamental for guaranteed Big Data experts to work.

  • Framework chairmen and programming designers.
  • Exchange and undertaking chiefs with experienced insight.
  • Large Data Hadoop Developers need to learn other vertical components. like testing, investigation, and the executives.
  • Proficient centralized servers, modelers, and specialists in testing.
  • Experts in business knowledge, information warehousing, and investigation Graduates will need to learn Big Data.

The confirmation preparation in Big Data Hadoop will help you with turning into a Big Data master. It will improve your abilities by furnishing you with exhaustive aptitude in Hadoop and the down-to-earth experience needed to tackle projects situated in the business progressively.

The accompanying figures will assist you with seeing Big Data development: Hadoop engineers have a normal compensation of INR 11,74,000. Associations are keen on enormous information and use Hadoop to store and dissect them. There is hence additionally a quick expansion popular for occupations in Big Data and Hadoop. Presently is the ideal spot for Big Data Hadoop web-based preparing if you have an interest in a vocation in this field.

Big Data Hadoop Certification preparation is intended to make you a Certified Big Data Practitioner by industry specialists. The course of Big Data Hadoop:
  • Inside and out data on the HD FS, YARN (Another Resource Negotiator) and Map Big Data, and Hadoop including the HDFS Cutting.
  • Exhaustive data on different devices, for example, Pig, Hive, Sqoop, Flume, Oozie, and HBase that fall inside Hadoop Ecologic.
  • The capacity to incorporate HDFS information utilizing Sqoop and Flume and to examine huge HDFS-based datasets of an assorted sort covering a few informational collections from various fields like banking, tea, etc.

You will have several days to dominate the subject if you as of now satisfy the requirements for Hadoop. It can take 2 to 90 days to learn Hadoop, be that as it may, if you gain without any preparation. In these cases, Big Data Hadoop Training is unequivocally suggested.

This course gives you data on the Hadoop environment and huge learning instruments and approaches to set you up to be a major data engineer and to finish your job. Your Big Data skills and hands-on aptitude are shown with the course affirmation. Hadoop accreditation will instruct you into biological system instruments like Hadoop, HDFS, MapReduce, Flume, Kafka, Hive, HBase, and so forth.

What are the performing goals of the Big Data and Hadoop Certification Training Course?

Hadoop is an Apache venture to store and handle Big Data. Hadoop stores Big Data over item equipment in an appropriate and lenient way. Hadoop's instruments are therefore used to resemble HDFS information processing. Because organizations understand the benefits of Big Data Analytics, Big Data and shadow experts have been sought after. Big Data and Hadoop specialists with Hadoop Ecosystem information and best practice on HDFS, MapReduce, Spark, HBase, Hive, Pig, Oozie, Sqoop, and Flume are looked for by organizations.

In this Big Data Hadoop Certification Training Course, what are you going to learn?

  • Hadoop and YARN essentials and compose applications.
  • Sparkle SQL, Streaming, Data Frame, RDD, GraphX, and MLlib composing. Spark applications HDFS MapReduce, Hive, Pig, Sqoop, Flume, and ZooKeeper Spark.
  • Avro information designs work.
  • Use Hadoop and Apache Spark to carry out genuine tasks.
  • Beset up to clear the confirmation with Big Data Hadoop.

What are the requirements for this Certification Training Course of Big Data Hadoop?

This Big Data class and expert Hadoop are not dependent upon prerequisites. Be that as it may, UNIX, SQL, Java, and Big Data Hadoop are generally fundamentals.

What are the job responsibilities of the Big Data and Hadoop Certification Training Course?

Expected set of responsibilities for Hadoop Developers:
  • Improvement and execution of Hadoop.
  • Hive and Pig are utilized for pre-preparing.
  • Making, developing, introducing, designing, and looking after Hadoop.
  • Examine a lot of data to discover new experiences.
  • Make information checking web benefits that are versatile and high-performing.

What will I get learn Big data and Hadoop Certification Training Course?

Some key Big data themes here you need to know:
  • Ideas OOPS.
  • Rudiments, for example, information types, punctuations, projecting sort, and so on Generics and assortments like all MapReduce programs.
  • The board of special cases.
  • Circling and contingent articulations.
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Overview of Hadoop Training in Indore

Learn Hadoop, Hadoop Administrator, Hadoop testing courses with Hadoop's for real-world training and investment and substantial employment support for you to become a Hadoop Architect. Fullest online Hadoop Training including HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Sqoop, and Flume. Attend this training course for Hadoop certification at our classroom or online training for the instructor. The Hadoop Course in Indore is an intensive training program that will familiarise you with Hadoop Distributed File System, Hadoop Clusters, Hadoop MapReduce, and our expert big data professionals' Big Data Processing Ecosystem. In addition, this Big Data Training allows you to gain evidence of the important tools that are highly-awaited in the big data area, such as PIG, HDFS, Pig, Apache Hive, Java, Apache Spark, Flume, and Sqoop.

Additional Info

Big data refers to enormous collections of data that are too complicated and vast for people or standard data management methods to understand. These massive amounts of data, when correctly evaluated using contemporary tools, provide organizations with the information they need to make educated decisions. Big data sets may now be used and tracked thanks to recent software advances. To the human eye, most of this user data would appear useless and disconnected. Big data analysis tools, on the other hand, can trace the links between hundreds of different types and sources of data to provide relevant business insight.

The 3 V's are three defining qualities of all large data sets :

Volume : Millions of unstructured, low-density data points must be included in big data sets. Big data companies can store anything from a few terabytes to hundreds of petabytes of customer data. Companies now have access to zettabytes of data thanks to cloud computing! Regardless of apparent importance, all data is preserved.Big data experts say that unexpected data might sometimes hold the answers to business issues.

Velocity refers to the rapid creation and use of large amounts of data. To give the most up-to-date insights, big data is received, processed, and interpreted in rapid succession. Many big data platforms can even capture and analyze data in real-time.

Variety : Within the same unstructured database, big data sets contain many sorts of data. Traditional data management systems rely on structured relational databases that include certain data kinds that are linked to other data types in predefined ways. To identify all relationships between all forms of data, big data analytics algorithms employ a variety of unstructured data sources. Big data methods frequently result in a more comprehensive picture of how each aspect interacts.

Hadoop is a distributed data processing framework for storing and analyzing large volumes of data that is dependable, distributed, and scalable. Hadoop allows you to link several computers into a network for storing and processing large datasets.

Hadoop's appeal stems from its ability to run on low-cost commodity hardware, whereas its competitors may require more costly gear to accomplish the same task. It's also free and open-source. Hadoop has made Big Data solutions accessible to individuals outside of the IT industry and has made Big Data solutions inexpensive for everyday companies. Hadoop is frequently used as a catch-all phrase for the whole Apache data science environment.

Why to choose Big Data & Hadoop?

    Hadoop is the greatest option for storing and processing massive data because Hadoop saves huge files as-is (raw) without any schema specification. High scalability - We can scale up to an unlimited number of nodes, greatly improving performance. Hadoop data is extremely accessible, even if the hardware fails.

  • Hadoop as a Big Data Technology Gateway :

    For Big Data analytics, Apache Hadoop is a cost-effective and dependable solution. Many businesses have embraced it. It is a full ecology, not just a single word. Apache Hadoop offers a huge ecosystem that caters to a variety of businesses. Hadoop was required by every firm, from digital start-ups to large corporations, to meet their business demands. Many components make up the Hadoop ecosystem, including HBase, Hive, Zookeeper, MapReduce, and so on. These Hadoop ecosystem components apply to a wide range of applications. Apache Hadoop will remain the backbone of the Big Data world, regardless of how many new technologies come and go. It serves as a point of entry for all Big Data technologies.To advance in the Big Data world, one must understand Hadoop and grasp other big data technologies that are part of the Hadoop ecosystem.

  • As a Disruptive Technology, Hadoop :

    In terms of dependability, scalability, affordability, performance, and storage, Hadoop is a good alternative to traditional data warehousing solutions. It has transformed data processing and ushered in a sea change in data analytics. In addition, the Hadoop ecosystem is always being improved and experimented with. Big Data and Apache Hadoop are taking the globe by storm, and we must ride with the wave if we do not want to be affected.

Roles And Responsibilities :

Companies all around the globe are looking for big data specialists that can analyze all types of data and turn it into usable knowledge. Hadoop Developers might have a variety of career titles and possibilities. Here is a list of job titles that will aid you in making the best selection by assisting you in selecting the appropriate Hadoop expert work position. Hadoop employment is available from a variety of industries, including financial corporations, retail groups, banks, and healthcare organizations.

1. Developer for Hadoop :

The actual coding or programming of Hadoop applications is the responsibility of a Hadoop Developer. This position is comparable to that of a Software Developer. The job functions are nearly identical, although the former falls within the Big Data umbrella.

2. Description for Hadoop Developers :

    A Hadoop Developer is responsible for a wide range of tasks. The following are the responsibilities of a Hadoop Developer:

  • Development and deployment of Hadoop
  • Hive and Pig for pre-processing
  • Creating, constructing, installing, configuring, and maintaining Hadoop
  • Analyze large data sets to discover new information
  • Create data monitoring web services that are scalable and high-performing.
  • Managing and installing HBase Test prototypes, as well as ensuring handoff to operational teams

3. Architect for Hadoop

To assist clients in answering their business concerns, Big Data Architect develops and implements efficient but cost-effective Big Data applications. Isn't that what Enterprise Architects and Solution Architects do? Big Data Architects, on the other hand, must examine classic data processing challenges through fresh lenses. You must adore numbers. There's a lot of information. There are both good and low-quality items. Being nimble also helps, especially when it comes to modern technologies. You should choose your tools carefully and be able to accept open-source technology in all of its positive and negative features.

4. Hadoop Architect Job Description :

    Hadoop Architects are charged with the enormous duty of defining where the corporation will go in terms of Big Data Hadoop implementation, as the name implies. They are responsible for planning, developing, and strategizing the roadmap, as well as determining how the company will proceed.

    As part of your Hadoop Architect job routine, you may anticipate encountering the following :

  • Assume full responsibility for the Hadoop Life Cycle throughout the enterprise.
  • Serve as a link between data scientists, engineers, and the demands of the company.
  • Perform a thorough study of the requirements and select the work platform only for that purpose.
  • A thorough understanding of Hadoop Architecture and HDFS is required.
  • MapReduce, HBase, Pig, Java, and Hive are all useful skills to have.
  • Assuring that the Hadoop solution of choice is successfully implemented.

5. Visualizer for Big Data :

A big data visualizer is a creative thinker that is familiar with UI design as well as other visualization abilities including typography, user experience design, and visual art design. One of the most crucial parts of big data is the capacity to display data in a way that it can be readily understood and new patterns and insights may be discovered.

6. After Data Visualization, Job Description :

The display of data pictorially or graphically is known as data visualization. It allows decision-makers to visually inspect analytics. This guide is intended to assist you in comprehending and using key Tableau ideas and approaches as you go from simple to sophisticated representations. After you've completed Data Visualization, you'll be able to:

7. Understand Tableau's jargon :
  • To build impressive visuals, use the Tableau interface.
  • Use Reference Lines to draw attention to specific aspects of your data.
  • To build focused and effective visualizations, utilize bins, hierarchies, sorts, sets, and filters.
  • Make visuals with a variety of measurements and dimensions.
  • Attach graphical data to interactive dashboards and share it with others.

8. Analyst for Big Data :

Whether it's sales figures, market research, logistics, or transportation expenses, data analysts transform numbers into clear business facts. Within a business system or IT system, a Data Analyst focuses on data analysis and problem resolution relating to data kinds and connections among data pieces.

9. Data Analyst Job Description :

    Data analysts, often known as business analysts, are in charge of completing complete lifecycle Big Data analysis. The following are some of the most significant responsibilities of a data analyst :

  • They keep an eye on performance and quality control plans to see where they can make changes.
  • Develop data analytics and other techniques to improve the efficiency and quality of statistical data.
  • Work with management to identify the most important business and information objectives.
  • Discover and outline endless opportunities for process improvement.

    Data scientists collaborate to tackle some of an organization's most difficult data challenges. These experts are adept in automating data collection and analysis processes, as well as employing inquisitive data exploration approaches to uncover previously undiscovered information that may have a significant impact on a company's performance.

  • A data scientist's job description is to be able to take a business problem and turn it into a data inquiry. Data science is the study of generalizable information extraction from data. Big data isn't the only type of data that may be studied in a Data Science course. It discusses the topics of business intelligence and analysis. Data scientists are responsible for a variety of tasks, including :

  • Machine learning techniques are used to build and optimize complicated data.
  • Data mining with cutting-edge techniques
  • Improving data gathering methods
  • Data for analysis is processed, cleansed, and verified for accuracy.
  • Performing ad-hoc analysis and presenting the results

Modules :

Hadoop Distributed File System (HDFS) Google's GFS article was released and HDFS was created as a result. The data will be split down into blocks and stored on nodes as part of the distributed design, according to the document. Another Resource Negotiator, Yarn, is used to schedule jobs and manage the cluster. Map Reduce is a framework that allows Java programs to do concurrent data processing using key-value pairs. The Map task transforms input data into a data collection that can be calculated in Key-value pairs. The output of the Map job is absorbed by the Reduce task, which subsequently outputs the required result.

Hadoop Common : These Java libraries are utilized by other Hadoop modules and are used to start Hadoop.

Certification :

  • The top 11 certifications in data analytics and big data
  • Associate in Microsoft Azure Data Science certification.
  • Associate Microsoft Certified Data Analyst
  • Data Scientist with Open Certification.
  • Using SAS 9, you may become a SAS Certified Advanced Analytics Professional.
  • Using SAS 9, you may become a SAS Certified Big Data Professional.

Pay Scale :

According to Randstad, the average salary for big data analytic specialists is 50 percent more than the average salary for other IT workers.The average pay for non-managerial big data analytic experts is 8.5 lakhs INR, while managers may make as much as 16 lakhs INR. These are the typical wages for big data capabilities such as Hadoop and spark. Salary is much higher for experienced individuals with profound analytical talent data scientists in non-managerial jobs earn an average of 12 lakhs, while managers earn an average of 18 lakhs. IT employees with analytic abilities may expect a salary increase of over 250 percent. When moving jobs to acquire professional personnel in the big data area, many organizations in India are willing to match the large increases in the industry that candidates are seeking for. According to Survey published by Analytics India, entry-level analytics specialists with a Master's Degree may take between 4 and 10 lakhs per year. Based on their experience in the relevant sector, experienced individuals with 3-10 years of experience may anticipate an average package of 10-30 lakhs per year.

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Key Features

ACTE Indore 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.


Syllabus of Hadoop Course in Indore
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
  • 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
  • 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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Hands-on Real Time Hadoop Projects

Project 1
Tourist Behaviour Analysis

This Big Data project is designed to analyze the tourist behaviour to identify tourists’ interests and most visited locations and accordingly, predict future tourism demands.

Project 2
Credit Scoring

The primary idea behind this project is to investigate the performance of both statistical and economic models. To do so, it will use a unique combination of datasets.

Project 3
Electricity Price Forecasting

This project is explicitly designed to forecast electricity prices by leveraging Big Data sets. The model exploits the SVM classifier to predict the electricity price.

Project 4
Busbeat Project

This project proposes data interpolation and network-based event detection techniques to implement early event detection with GPS trajectory data successfully.

Our Best Hiring Placement Partners

ACTE Indore give positions Backing. We have committed situation Official dealing with the Understudies arrangement. Far beyond we have tie-ups with such countless IT Organizations where the imminent HRs and Bosses reach us for situations.
  • We have many tie-ups with organizations across the city, subsequently, understudies land lucrative positions through limitless situation calls and walk-ins.
  • Industry specialists set them up for arrangements through delicate abilities and mock meeting meetings. Big Data and Hadoop Training in Indore in Positions will help you arrive at the highest point of the corporate progressive system.
  • placement offices need to make a solid effort to snatch seats for their wards well ahead of time in the problem of vulnerability. Understudies stand by pitifully for the hour of enrolment of entry level position.
  • Placement opportunity and with 1200+ organization of IT organizations.
  • Placement Cell gives a brought stage up in Demonstrable skill, character prepping for the growing abilities or more all the making a quality individual to empower them to focus on the shoulder with best the corporate world.
  • Placement Cell is set up with full-time situation expert, and offers understudies work arrangement help. Position Cell administrations incorporate vocation investigation, work preparation, profession arranging, vocation guiding, expertise advancement, ID of business openings, work arrangement, and continuous help.

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.

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About  Adequate Hadoop Mentor

  • Our Big Data and Hadoop Training in Indore have worked with over 600+ small and major companies to help you kick-start and grow your career with Google, CTS, TCS, IBM, and other companies. It enables us to place our applicants in top multinational corporations all around the world.
  • We sought after programming language because of its capacity of getting and handling information continuous. Accordingly, sites are stages to show content as well as execute errands of online applications. This is the principle justification its prevalence in the business.
  • ACTE makes specialists in the field. Because of the prominence of this language, learners must be knowledgeable in future patterns. Thus, our educational program is in accordance with current mechanical prerequisites.
  • Experts at our have gone through quite a while in the business. Subsequently, they are insight in both topic and certifiable industry applications.
  • Learners get the chance to deal with genuine ventures of organizations in the field. It gives them involved insight of their jobs and obligations.
  • Learners who need to profit with master direction, involved insight and limitless arrangement openings should try out Big-data-and-hadoop-training-in-indore.

Hadoop Course Reviews

Our ACTE Indore 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.



"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"


Software Engineer

Hi, I am Durga . I done my Hadoop course in ACTE. The best institute for learning Hadoop and faculty is very very good.i can surely tell that i have taken a right step in joining ACTE. I feel it is very good online training for Hadoop Modules. "I am fully satisfied with the training........". Thank u ACTE in Indore.


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.



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.


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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  • 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
    • Gives
    • 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's E-commerce payment system Login or directly walk-in to one of the ACTE branches in India
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