Why Big data Bundle?

IDC predicts that Big Data Technology and Services Market will grow at 26.4 % annually to $41.5 billion through 2018.

Demand for Hadoop and related technologies are projected to exceed supply by more than 50 percent by 2018. The exponential growth in data across various industries and advanced processing capabilities present Big Data and Hadoop Professionals with sought after positions in big data analysis.
Hadoop is not just a product or a platform; it is an ecosystem of open products, technologies, tools, and platforms that work together to derive insights from unstructured or semi-structured data distributed over many computers. Every day, 2.5 quintillion bytes of data get created globally from different transactions and devices.
These following 4 most popular and useful Big Data technologies packaged as self-paced online learning modules spanning 232 lectures consisting of 37.5 hours of content will enable you to confidently handle Big Data problems in multiple scenarios.

Hadoop & MapReduce for
Big Data Problems

13 Hrs | 71 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Using MapReduce – the most popular open source parallel programming model for processing large datasets, you will learn how to do efficiently process large amounts of data spread across Hadoop Clusters. With 71 lectures consisting of 13 hours of content that are accessible 24X7, you will be able to setup your own Hadoop cluster and perform multiple parallel processing real world assignments.
COURSE OUTLINE +

Hive for Big Data Processing

15 Hrs | 86 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Hive is a data warehousing tool built on top of Hadoop that helps you to take advantage of distributed computing. With 86 lectures consisting of 15 hours of content, you will be able to write complex analytical queries, use partitioning and bucketing concepts to optimize queries and understand how Hive, HDFS and MapReduce work together.

COURSE OUTLINE +

HBase – The Hadoop Database

4.5 Hrs | 41 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Apache HBase is an open-source distributed database built on top of Hadoop Distributed File System(HDFS). With 41 lectures consisting of 4.5 hours of content that are accessible 24X7, you will be able to setup a database for your application, create and access data from HBase, integrate HBase with MapReduce for data processing tasks and understand the role of HBase in the Hadoop ecosystem.

COURSE OUTLINE +

Pig for Wrangling Big Data

5 Hrs | 34 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Apache Pig can execute its Hadoop jobs in MapReduce. With 34 lectures consisting of 5 hours of content that are accessible 24X7, you can work with unstructured data to extract information, transform and store in a usable form, write intermediate level Pig scripts and optimize operations to work on large data sets.

COURSE OUTLINE +

Oozie: Workflow Scheduling for Big Data Systems

3 Hrs | 23 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

The Oozie framework helps you to manage thousands of jobs in an orchestrated manner. With 23 lectures consisting of 3 hours of content that are accessible 24X7,you will install & setup Oozie, configure workflows to run Hadoop jobs, create time-triggered & data-triggered Workflows as well as build & optimize data pipelines using Bundles.

COURSE OUTLINE +

Scalable Programming with Scala & Spark

8.5 Hrs | 51 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Using Scala & Spark together will help you to effectively analyze data in an interactive environment with fast feedback. With 51 lectures consisting of 8.5 hours of content that are accessible 24X7,you will learn functional programming constructs in Scala, use the different libraries & features of Spark for various analytics & machine learning tasks and build Scala applications.

COURSE OUTLINE +

Flume & Sqoop for Ingesting Big Data

2 Hrs | 16 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Flume and Sqoop help you to efficiently Import Data to HDFS, HBase & Hive From a Variety of Sources. With 16 lectures consisting of 2 hours of content that are accessible 24X7, you will use Flume to ingest data to HDFS & HBase, optimize Sqoop to import data from MySQL to HDFS & Hive and ingest data from a variety of sources including HTTP, Twitter and MySQL.

COURSE OUTLINE +

Spark for Data Science in Python

8 Hrs | 52 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Spark provides you a single interactive environment to work with large amounts of data, run machine learning algorithms and other functions. With 52 lectures consisting of 8 hours of content that are accessible 24X7, you will implement complex algorithms using Spark, work with a variety of datasets and employ different features & libraries of Spark.

COURSE OUTLINE +

The Cassandra Distributed Database

5.5 Hrs | 44 Lessons | WATCH VIDEO

₹ 2,599.00 Enroll Now

Cassandra is a highly scalable, high-performance distributed database designed to handle large amounts of data. With 44 lectures consisting of 5.5 hours of content that are accessible 24X7, you will set up and manage a cluster using Cassandra Cluster Manager, understand restrictions on queries, learn architecture and storage components and work on a live project.

COURSE OUTLINE +

ScholarsPro offers Big Data Hadoop (Developer) Live Online Group Training. Please click here for Details

 WHO SHOULD JOIN?

  • This course is designed for individuals seeking to gain expertise in the concepts of big data, tools and the platform of Hadoop needed for processing large data sets.
  • If you are an IT professional with a minimum of 2 years’ experience in programming with an interest in developing a career in analytics, this course is a good place to start.
  • If you are from other technology backgrounds and have a need to work on big data to derive insights, this course will be of help.
  • Professionals working in Data Warehousing / Mining technologies will be able to advance their career in Big Data Engineering and Data Science roles.

Prerequisites for Big Data Bundle Training

Though not mandatory, basic knowledge of Java or other programming language is recommended.

Meet the Scholars

Janani Ravi, Vitthal Srinivasan, Swetha Kolalapudi and Navdeep Singh—who have honed their tech expertise at Google and Flipkart have put these 4 Big Data technologies together. The team believes it has distilled the instruction of complicated tech concepts into funny, practical, engaging courses, and is excited to be sharing its content with eager students.

YOUR SUCCESS IS OURS TOO!

Helly shah
Helly shahContent writer
“Digital marketing course by scholars helps me to gain knowledge in the field of marketing,Trainer was very nice and adjustable ...
Diksha thakur
Diksha thakurStudent
NMIMS
“Very supportive ands cooperative trainer ,Pranav sir always helps us to improvise the things .The course is very knowledgable which ...
Aayush bhardwaj
Aayush bhardwajStudent
NMIMS
“The DM course study material, classes was very helpful in terms of knowledge and exposure about the SMO,SEO,TRainer ...
Bhavna Singh
Bhavna SinghMarket development SE
Snapdeal
“Great learning by the trainer ,satisfied with the delivery of content.”
Baljinder sachdeva
Baljinder sachdevaMarketing head at
IVF fertility centre
“Great learning by the trainer ,satisfied with the delivery of content.”
Sanjeev Sharma
Sanjeev SharmaManager
Evalueserve, India
The course curriculum, study material and classes for Business Analytics course were very helpful in terms of knowledge and exposure ...
Sanjay Sinha
Sanjay Sinha Secretary ICAS,
India
“SchoalrsPro good place to learn R through online course. Great environment and very nice faculty.  All the best!”
Nipun Raj
Nipun RajBranch Manager
Reliance Capital, India
“My experience is very good with ScholarsPro. Trainer of Digital Marketing is very much supportive and knowledgeable.”
Manish
ManishAssistant Manager
Barclays Bank, India
“Incredible Trainer! I have been trying to learn SAS since 1 month on my own. Everything got jumbled up. Thanks ...
Amit Kumar Singh
Amit Kumar SinghSoftware Development Engineer
Allegis Services, India
“I would like to thank you for your support. I enjoyed your Hadoop classes.”
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FAQs

This bundle is designed for individuals seeking to gain expertise in the concepts of big data, tools and the platform of Hadoop needed for processing large data sets. However, basic understanding of Java or some programming is recommended.

These courses are ideal for engineers, scientists, researchers, and business analysts who are keen to grow their career in Big Data and Analytics.

It is not mandatory that you need a technical background to learn Hadoop. If you have a need to derive insights from large volume of data in your current job or if you like to switch to a career in Data Science or Analytics, thesemodules will help you.

A certification in Big Data & Hadoop can definitely complement your job search. However having a few years’ experience will be an added advantage for most of the practical implementation of Hadoop.

Definitely! In fact you can consider Hadoop Administration roles who manages infrastructure, Hadoop Clusters etc.

While a basic working knowledge of Java will be of help, it is not mandatory to know Java programming for learning Hadoop. Some of the Hadoop components like Pig, Hive etc. can be learned without knowledge of Java. There are some rare requirements to use Java which can be learned easily.

The purpose of these modules is to provide high level understanding and the capabilities:

  • Hadoop & MapReduce for Big Data Problems
  • Hive for Big Data Processing
  • HBase – The Hadoop Database
  • Pig for Wrangling Big Data
  • Oozie: Workflow Scheduling for Big Data Systems
  • Scalable Programming with Scala & Spark
  • Flume & Sqoop for Ingesting Big Data
  • From 0 to 1 : Spark for Data Science in Python
  • From 0 to 1 : The Cassandra Distributed Database
  • Access 71 lectures & 13 hours of content 24/7
  • Set up your own Hadoop cluster using virtual machines (VMs) & the Cloud
  • Understand HDFS, MapReduce & YARN & their interaction
  • Use MapReduce to recommend friends in a social network, build search engines & generate bigrams
  • Chain multiple MapReduce jobs together
  • Write your own customized partitioner
  • Learn to globally sort a large amount of data by sampling input files
  • Access 86 lectures & 15 hours of content 24/7
  • Write complex analytical queries on data in Hive & uncover insights
  • Leverage ideas of partitioning & bucketing to optimize queries in Hive
  • Customize Hive w/ user defined functions in Java & Python
  • Understand what goes on under the hood of Hive w/ HDFS & MapReduce
  • Access 41 lectures & 4.5 hours of content 24/7
  • Set up a database for your application using Hbase.
  • Integrate HBase w/ MapReduce for data processing tasks
  • Create tables, insert, read $ & delete data from HBase.
  • Get a complete understanding of HBase & its role in the Hadoop ecosystem.
  • Explore CRUD operations  in the shell, & with JAVA API
  • Access 34 lectures & 5 hours of content 24/7
  • Clean up server logs using Pig
  • Work w/ unstructured data to extract information, transform it, & store it in a usable form
  • Write intermediate level Pig scripts to munge data
  • Optimize Pig operations to work on large data sets
  • Access 23 lectures & 3 hours of content 24/7
  • Install & set up Oozie
  • Configure Workflows to run jobs on Hadoop
  • Create time-triggered & data-triggered Workflows
  • Build & optimize data pipelines using Bundles
  • Access 51 lectures & 8.5 hours of content 24/7
  • Use Spark for a variety of analytics & machine learning tasks
  • Understand functional programming constructs in Scala
  • Implement complex algorithms like PageRank & Music Recommendations
  • Work w/ a variety of datasets from airline delays to Twitter, web graphs, & Product Ratings
  • Use the different features & libraries of Spark, like RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming, & GraphX
  • Write code in Scala REPL environments & build Scala applications w/ an IDE
  • Access 16 lectures & 2 hours of content 24/7
  • Use Flume to ingest data to HDFS & HBase
  • Optimize Sqoop to import data from MySQL to HDFS & Hive
  • Ingest data from a variety of sources including HTTP, Twitter & MySQL
  • Access 52 lectures & 8 hours of content 24/7
  • Use Spark for a variety of analytics & machine learning tasks
  • Implement complex algorithms like PageRank & Music Recommendations
  • Work w/ a variety of datasets from airline delays to Twitter, web graphs, & product ratings
  • Employ all the different features & libraries of Spark, like RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming & GraphX
  • Access 44 lectures & 5.5 hours of content 24/7
  • Set up & manage a cluster using the Cassandra Cluster Manager (CCM)
  • Create keyspaces, column families, & perform CRUD operations using the Cassandra Query Language (CQL)
  • Design primary keys & secondary indexes, & learn partitioning & clustering keys
  • Understand restrictions on queries based on primary & secondary key design
  • Discover tunable consistency using quorum & local quorum
  • Learn architecture & storage components: Commit Log, MemTable, SSTables, Bloom Filters, Index File, Summary File & Data File
  • Build a Miniature Catalog Management System using the Cassandra Java driver