Big Data Hadoop, Spark, Storm, and Scala Training

BY
IBM via Intellipaat

Gain expertise in Big Data Hadoop, Spark, Storm, and Scala and land upon the exciting job opportunities through the certification course by Intellipaat.

Mode

Online

Fees

₹ 19950

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study, Virtual Classroom
Mode of Delivery Video and Text Based
Frequency of Classes Weekdays, Weekends

Course overview

In the technology-driven world, programmers have made their place indispensable. With the advanced technologies, they are working on the smart world. Computer languages form the basis of such advancement. Big Data Hadoop, Spark, Storm, and Scala Training is the online certification course by Intellipaat which is one such initiative to prepare the people who are willing to be a part of the change. The program offers 114 hours of self-paced videos and 166 hours of project training. Further, the learner has the advantage of a flexible schedule and mentor support. 

The mentors of this course are experienced and shall guide the candidates throughout the course. In addition to this, they also provide corporate clients to upskill their workforce and keep them in sync with the changing technology and digital landscape. After the completion of the course, the candidate shall receive Big Data Hadoop, Spark, Storm, and Scala Training certification by Intellipaat. The certification shall be recognized in more than 50 MNCs and will help the candidate to get themselves a desirable job. 

The highlights

  • 100% online course 
  • Flexible learning hours
  • Instructor-led training 
  • Certification
  • 114 hours self-paced videos
  • 166 hours project training
  • Lifetime free upgrade
  • Job assistance

Program offerings

  • Online course
  • 114 hours of self-paced videos and 166 hours of project training
  • Convenient learning
  • Video demonstration
  • Assessments
  • Certification
  • Job assistance.

Course and certificate fees

Fees information
₹ 19,950

Big Data Hadoop, Spark, Storm, and Scala Training certification fee depending upon the mode of learning opted by the candidate. The course offers a subscription to the candidates and also a free lifetime upgrade to the candidates. 

Fee structure for Big Data Hadoop, Spark, Storm, and Scala Training

Course name 

Fee in USD

Big Data Hadoop, Spark, Storm, and Scala Training self-paced learning 

₹ 19,950

certificate availability

Yes

certificate providing authority

IBM

Eligibility criteria

Certification Qualifying Details 

The Big Data Hadoop, Spark, Storm, and Scala Training online course is designed for the overall development of the programming language. The candidate can either choose self-paced training, online classroom learning. Corporate learning is for pushing up the employees as per the current requirement of the market. The candidate must complete the practical and academic learning assessment for Big Data Hadoop, Spark, Storm, and Scala Training certification from Intellipaat. The candidate shall receive a certificate after qualifying for the quiz with a 60% score and performing the practical assessments.

What you will learn

Programming skills Knowledge of big data Knowledge of apache spark

Big Data Hadoop, Spark, Storm, and Scala Training certification course is the combo for the learners who want to learn these languages completely. This is the comprehensive training that allows the learner to dig deep into the knowledge of Big Data analysis and the tools. Moreover, the real-world projects shall help the learner to grab practical skills. After the completion of the course, the candidate shall become proficient at Big Data programming, build the clusters from Hadoop. Performing the high-speed data processing from Apache spark and grabs full understanding of Scala. At the end of the program, the learner shall become proficient in the following tasks:

  • The architecture of the Hadoop 
  • The Hadoop cluster setup and maintenance
  • Data science and project life cycle
  • MapReduce programs
  • Impala, Zookeeper, YARN, Flume, Oozie
  • Working on real-time Hadoop projects 
  • Deploying the Hadoop cluster 
  • Writing the Spark cluster in the Python, Java, cluster
  • Scalp programming and implementation
  • Trident spouts and filter in Storm
  • Apache Storm architecture

The syllabus

Hadoop Installation and Setup

  • The architecture of Hadoop 2.0 cluster
  • What is High Availability and Federation
  • How to set up a production cluster
  • Various shell commands in Hadoop
  • Understanding configuration files in Hadoop2.0
  • Installing single node cluster with Cloudera Manager and understanding Spark,
  • Scala, Sqoop, Pig and Flume

Introduction to Big Data Hadoop and Understanding HDFS and MapReduce

  • Introducing Big Data and Hadoop
  • What is Big Data and where does Hadoopfit in
  • Two important Hadoop ecosystem components, namely, Map Reduce andHDFS,
  • In-depth Hadoop Distributed File System –Replications, Block Size, Secondary Name node, High Availability, and 
  • In-depth YARN – resource manager and node manager

Deep Dive in Mapreduce

  • Learning the working mechanism of MapReduce
  • Understanding the mapping and reducing stages inMR
  • Various terminologies in MR like Input Format, Output Format, Partitioners, Combiners, Shuffle, and Sort
  • Hands-on Exercise

Introduction to Hive

  • Introducing Hadoop Hive, detailed architecture ofhive
  • Comparing Hive with Pig andRDBMS
  • Working with Hive Query Language, creation of database, table, Group by and
  • other clauses
  • Various types of Hive tables, HCatalog, storing the Hive Results, Hive
  • partitioning and Buckets

Advance Hive and Impala

  • Indexing in Hive, the Map Side Join inHive
  • Working with complex data types, the Hive User-defined Functions
  • Introduction to Impala, comparing Hive with Impala, the detailed architecture of Impala

Introduction to Pig

  • Apache Pig introduction, its various features
  • Various data types and schema in Hive
  • The available functions in Pig, Hive Bags, Tuples and Fields

Flume, Sqoop and HBase

  • Apache Sqoop introduction, overview, importing and exporting data, performance improvement with Sqoop
  • Sqoop limitations, introduction to Flume and understanding the architecture of Flume and what is HBase and the CAP theorem

Flume and what is HBase and the CAP theorem Hadoop Administration – Multi-node Cluster Setup Using Amazon EC2

  • Create a 4-node Hadoop cluster setup
  • Running the MapReduce Jobs on the Hadoopcluster
  • Successfully running the MapReduce code and working with the Cloudera Manager setup

Hadoop Administration – Cluster Configuration

  • The overview of Hadoop configuration, the importance of Hadoop configuration file, the various parameters and values of configuration
  • The HDFS parameters and MapReduce parameters
  • Setting up the Hadoop environment, the Include and Exclude Configuration files
  • The administration and maintenance of NameNode, DataNode directory structures and files
  • What is a File system image and understanding Editlog.

Hadoop Administration – Maintenance, Monitoring and Troubleshooting

  • Introduction to the checkpoint procedure
  • NameNode failure and how to ensure the recovery procedure, Safe Mode, Metadata and Data backup
  • Various potential problems and solutions, what to look for, and how to add and remove nodes

ETL Connectivity with Hadoop Ecosystem

  • How ETL tools work in Big Data Industry
  • Introduction to ETL and data warehousing
  • Working with prominent use cases of Big Data in ETL industry and end-to-end ETL PoC showing Big Data integration with ETLtool

Project Solution Discussion and Cloudera Certification Tips and Tricks

  • Working towards the solution of the Hadoop project solution, its problem statements and the possible solution outcomes
  • Preparing for the Cloudera certifications, points to focus for scoring the highest marks and tips for cracking Hadoop interview questions

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