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- About the Course
- Curriculam
- Certification
- FAQ's
Course Nex Big Data Hadoop online training is designed to help you become a top Hadoop developer. During this course, our expert instructors will help you:
Course Details
- Master the concepts of HDFS and MapReduce framework
- Understand Hadoop 2.x Architecture
- Setup Hadoop Cluster and write Complex MapReduce programs
- Learn data loading techniques using Sqoop and Flume
- Perform data analytics using Pig, Hive and YARN
- Implement HBase and MapReduce integration
- Implement Advanced Usage and Indexing
- Schedule jobs using Oozie
- Implement best practices for Hadoop development
- Work on a real life Project on Big Data Analytics
- Understand Spark and its Ecosystem
- Learn how to work in RDD in Spark
Who should go for this Hadoop Course?
Market for Big Data analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Here are the few Professional IT groups, who are continuously enjoying the benefits moving into Big data domain:
- Developers and Architects
- BI /ETL/DW professionals
- Senior IT Professionals
- Testing professionals
- Mainframe professionals
- Freshers
What are the pre-requisites for the Hadoop Course?
As such, there are no pre-requisites for learning Hadoop. Knowledge of Core Java and SQL will be beneficial, but certainly not a mandate. If you wish to brush-up Core-Java skills, Course Nex offer you a complimentary self-paced course, i.e. "Java essentials for Hadoop" when you enroll in Big Data Hadoop Certification course.
How will I do practicals in Online Training?
For practicals, we will help you to setup Course Nex's Virtual Machine in your System with local access. The detailed installation guide will be present in LMS for setting up the environment. In case, your system doesn't meet the pre-requisites e.g. 4GB RAM, you will be provided remote access to the Course Nex cluster for doing practical. For any doubt, the 24*7 support team will promptly assist you. Course Nex Virtual Machine can be installed on Mac or Windows machine and the VM access will continue even after the course is over, so that you can practice.
Case-Studies
Towards the end of the course, you will work on a live project where you will be using PIG, HIVE, HBase and MapReduce to perform Big Data analytics. Following are a few industry-specific Big Data case studies that are included in our Big Data and Hadoop Certification e.g. Finance, Retail, Media, Aviation etc. which you can consider foryour project work:
1. Understanding Big Data and Hadoop
Learning Objectives - In this module, you will understand Big Data, the limitations of the existing solutions for Big Data problem, how Hadoop solves the Big Data problem, the common Hadoop ecosystem components, Hadoop Architecture, HDFS, Anatomy of File Write and Read, how MapReduce Framework works.
Topics - Big Data, Limitations and Solutions of existing Data Analytics Architecture, Hadoop, Hadoop Features, Hadoop Ecosystem, Hadoop 2.x core components, Hadoop Storage: HDFS, Hadoop Processing: MapReduce Framework, Hadoop Different Distributions.
2. Hadoop Architecture and HDFS
Learning Objectives - In this module, you will learn the Hadoop Cluster Architecture, Important Configuration files in a Hadoop Cluster, Data Loading Techniques, how to setup single node and multi node hadoop cluster.
Topics - Hadoop 2.x Cluster Architecture - Federation and High Availability, A Typical Production Hadoop Cluster, Hadoop Cluster Modes, Common Hadoop Shell Commands, Hadoop 2.x Configuration Files, Single node cluster and Multi node cluster set up Hadoop Administration.
3. Hadoop MapReduce Framework
Learning Objectives - In this module, you will understand Hadoop MapReduce framework and the working of MapReduce on data stored in HDFS. You will understand concepts like Input Splits in MapReduce, Combiner & Partitioner and Demos on MapReduce using different data sets.
Topics - MapReduce Use Cases, Traditional way Vs MapReduce way, Why MapReduce, Hadoop 2.x MapReduce Architecture, Hadoop 2.x MapReduce Components, YARN MR Application Execution Flow, YARN Workflow, Anatomy of MapReduce Program, Demo on MapReduce. Input Splits, Relation between Input Splits and HDFS Blocks, MapReduce: Combiner & Partitioner, Demo on de-identifying Health Care Data set, Demo on Weather Data set.
4. Advanced MapReduces
Learning Objectives - In this module, you will learn Advanced MapReduce concepts such as Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format and XML parsing.
Topics - Counters, Distributed Cache, MRunit, Reduce Join, Custom Input Format, Sequence Input Format, Xml file Parsing using MapReduce.
5. Pig
Learning Objectives - In this module, you will learn Pig, types of use case we can use Pig, tight coupling between Pig and MapReduce, and Pig Latin scripting, PIG running modes, PIG UDF, Pig Streaming, Testing PIG Scripts. Demo on healthcare dataset.
Topics - About Pig, MapReduce Vs Pig, Pig Use Cases, Programming Structure in Pig, Pig Running Modes, Pig components, Pig Execution, Pig Latin Program, Data Models in Pig, Pig Data Types, Shell and Utility Commands, Pig Latin : Relational Operators, File Loaders, Group Operator, COGROUP Operator, Joins and COGROUP, Union, Diagnostic Operators, Specialized joins in Pig, Built In Functions ( Eval Function, Load and Store Functions, Math function, String Function, Date Function, Pig UDF, Piggybank, Parameter Substitution ( PIG macros and Pig Parameter substitution ), Pig Streaming, Testing Pig scripts with Punit, Aviation use case in PIG, Pig Demo on Healthcare Data set.
6. Hive
Learning Objectives - This module will help you in understanding Hive concepts, Hive Data types, Loading and Querying Data in Hive, running hive scripts and Hive UDF.
Topics - Hive Background, Hive Use Case, About Hive, Hive Vs Pig, Hive Architecture and Components, Metastore in Hive, Limitations of Hive, Comparison with Traditional Database, Hive Data Types and Data Models, Partitions and Buckets, Hive Tables(Managed Tables and External Tables), Importing Data, Querying Data, Managing Outputs, Hive Script, Hive UDF, Retail use case in Hive, Hive Demo on Healthcare Data set.
7. Advanced Hive and HBase
Learning Objectives - In this module, you will understand Advanced Hive concepts such as UDF, Dynamic Partitioning, Hive indexes and views, optimizations in hive. You will also acquire in-depth knowledge of HBase, HBase Architecture, running modes and its components.
Topics - Hive QL: Joining Tables, Dynamic Partitioning, Custom Map/Reduce Scripts, Hive Indexes and views Hive query optimizers, Hive : Thrift Server, User Defined Functions, HBase: Introduction to NoSQL Databases and HBase, HBase v/s RDBMS, HBase Components, HBase Architecture, Run Modes & Configuration, HBase Cluster Deployment.
8.Advanced HBase
Learning Objectives - This module will cover Advanced HBase concepts. We will see demos on Bulk Loading , Filters. You will also learn what Zookeeper is all about, how it helps in monitoring a cluster, why HBase uses Zookeeper.
Topics - HBase Data Model, HBase Shell, HBase Client API, Data Loading Techniques, ZooKeeper Data Model, Zookeeper Service, Zookeeper, Demos on Bulk Loading, Getting and Inserting Data, Filters in HBase.
9. Processing Distributed Data with Apache Spark
Learning Objectives - In this module you will learn Spark ecosystem and its components, how scala is used in Spark, SparkContext. You will learn how to work in RDD in Spark. Demo will be there on running application on Spark Cluster, Comparing performance of MapReduce and Spark.
Topics - What is Apache Spark, Spark Ecosystem, Spark Components, History of Spark and Spark Versions/Releases, Spark a Polyglot, What is Scala?, Why Scala?, SparkContext, RDD.
10. Oozie and Hadoop Project
Learning Objectives - In this module, you will understand working of multiple Hadoop ecosystem components together in a Hadoop implementation to solve Big Data problems. We will discuss multiple data sets and specifications of the project. This module will also cover Flume & Sqoop demo, Apache Oozie Workflow Scheduler for Hadoop Jobs, and Hadoop Talend integration.
Topics - Flume and Sqoop Demo, Oozie, Oozie Components, Oozie Workflow, Scheduling with Oozie, Demo on Oozie Workflow, Oozie Co-ordinator, Oozie Commands, Oozie Web Console, Oozie for MapReduce, PIG, Hive, and Sqoop, Combine flow of MR, PIG, Hive in Oozie, Hadoop Project Demo, Hadoop Integration with Talend.
Course Nex Certification:
Once you are successfully through the project (Reviewed by a Course Nex expert), you will be awarded with Course Nex’s Big Data and Hadoop certificate.
Course Nex certification has industry recognition and we are the preferred training partner for many MNCs e.g.Cisco, Ford, Mphasis, Nokia, Wipro, Accenture, IBM, Philips, Citi, Ford, Mindtree, BNYMellon etc. Please be assured.
How will I execute the Practicals?
We will help you to setup Course Nex's Virtual Machine in your System with local access. The detailed installation guides are provided in the LMS for setting up the environment. In case your system doesn't meet the pre-requisites e.g. 4GB RAM, you will be provided remote access to the Course Nex cluster for the practicals. For any doubt, the 24*7 support team will promptly assist you.Course Nex Virtual Machine can be installed on Mac or Windows machine.
Who are the Instructors?
All our instructors are working professionals from the Industry and have at least 10-12 yrs of relevant experience in various domains. They are subject matter experts and are trained by Coursenex for providing online training so that participants get a great learning experience.
What if I miss a class?
You will never lose any lecture. You can choose either of the two options: 1. View the recorded session of the class available in your LMS. 2. You can attend the missed session, in any other live batch.
What if I have queries after I complete this course?
Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.
Is Java a pre-requisite to learn Big Data and Hadoop?
You can master Hadoop, irrespective of your IT background. While basic knowledge of Core Java and SQL might help, it is not a pre-requisite for learning Hadoop. In case you wish to brush-up your Java skills, Course Nex offers you a complimentary self-paced course: "Java essentials for Hadoop".
I am from Admin background, is the Big data and Hadoop course a right choice?
Professionals with Administration experience can take up "Hadoop Administration" course training. It will be a natural career progression. If you are planning for Big Data Architect role then you may consider both Hadoop developer and Hadoop Administration training, sequentially.
Do you provide placement assistance?
Coursenex is the largest online education company and lots of recruitment firms contacts us for our students profiles from time to time. Since there is a big demand for this skill, we help our certified students get connected to prospective employers. We also help our customers prepare their resumes, work on real life projects and provide assistance for interview preparation. Having said that, please understand that we don't guarantee any placements however if you go through the course diligently and complete the project you will have a very good hands on experience to work on a Live project.
Can I Install Hadoop on my Mac Machine?
Yes, it is possible. Detailed installation guides are provided in the LMS for setting up the environment
Can I Install Hadoop on my Windows Machine?
Absolutely yes! One can always use Windows to work on Hadoop. You need to install Oracle Virtual Box on your Windows machine and then you can import Course Nex Virtual Machine in it, which we will provide you.
What are the system requirements to install Hadoop environment?
Your system should have 4GB RAM, a processor better than core 2 duo. In case, your system falls short of these requirements, we can provide you remote access to our Hadoop Cluster.
Can I get the recorded sessions of a class from some other batches before attending a live class?
Yes, this can be done. Moreover, this ensures that when you will start with your actual Batch, the concepts explained during the classes will not be totally new to you. Because you would have already done some preparation at your end, you will be in the position to ask the right questions and get the most out of the course.
How can I request for a support session?
Requesting for a support session is a very simple process. As soon as you join the course, the contact number and email-id of the support team will be available in your LMS. Just a phone call or email will solve the purpose.
Can I attend a demo session ?
We have limited number of participants in a live session to maintain the Quality Standards, hence, unfortunately participation in a live class without enrolment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in the class.
How can I request for a support session?
Requesting for a support session is a very simple process. As soon as you join the course, the contact number and email-id of the support team will be available in your LMS. Just a phone call or email will solve the purpose.
Are these training sessions conducted Online or via Physical classroom?
These classes will be completely Online Live Instructor-led Interactive sessions. You will have chat option available to discuss your queries with instructor during a class.
What is the schedule of the classes and how many hours effort would I need to put in every week?
Depending on the batch you select, Your Live Classes will be held either every weekend for 5 weeks or for 15 weekdays. It would typically be 6-7 hours of effort needed each week post live sessions. This shall comprise hands-on assignments.
How much internet speed is required to attend the LIVE classes?
1 Mbps of internet speed is preferable to attend the LIVE classes.
What are the payment options?
You can pay by Credit Card, Debit Card or Net Banking from all the leading banks. We use a CCAvenue Payment Gateway. For USD payment, you can pay by PayPal. We also have EMI options available.
What if I have more queries?
You can give us a CALL at +1 415-912-7801 OR email at info@Coursenex.com
Online Classroom
Starts From - January 21st, 2017.
Days - Saturday & Sunday (5 Weeks)
Time - 09.00 AM - 12.00PM
Fees - Rs.15,999 / Rs.18,999
Course Features
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+1 415-912-7801
Big Data Hadoop training will make you expert in HDFS, Yarn, MapReduce, Pig, Hive, HBase, Oozie, Flume and Sqoop using real-time use cases on Retail, Social Media, Aviation, Tourism, Finance domain.