Big Data Developer Course

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About Course

Master the most in-demand big data skills: Hadoop, Sqoop, Hive, Spark, Scala, Cassandra, HBase, NIFI, Kafka and more

Big Data Developers are in high demand and it’s only going to increase as data and AI grows all across the various sectors. Mastering the skills needed to become a Big Data Engineer can be overwhelming. That’s why we created “The Big Data Developer Course” with the help of industry experts. This course provides an end-to-end implementation of the most in-demand Big Data skills, including Hadoop, Spark, Kafka, Cassandra, and more. With more than 40 hours of hands-on training, you’ll start with the basics and work your way up to production-level deployment, troubleshooting, and performance improvement.

We cover everything from local development to integrating with complex data sources, such as NOSQL databases, and even streaming data. Our team is available to address any questions you may have, and our tutorials are all explained with examples. By the end of this course, you’ll be a Big Data expert, ready to take on any job in the industry. Don’t miss this opportunity to join the world of Big Data!

Here is a short description of what you will be learning in this course:

Understand the world of Big Data. What is Big data and why it is important
Understand and learn the concepts behind Hadoop. Understand its architecture
Install the software and start writing code
Learn important Hadoop Commands
Learn the file formats and understand when to use each of the file formats
Dive deep into Sqoop- a tool used for transferring data between RDBMS and HDFS
Dive deep into Hive- a tool used for querying the data on HDFS
Learn Scala – a top programming language
Dive deep into Spark which is very hot in the market
Learn NOSQL Databases – Cassandra and HBase and integrate them with Spark
Work with Complex data and process them effectively
Make your code production ready and deploy them onto the cluster
Learn Apache NIFI- a powerful and scalable open source tool for data routing
Work with Streaming data
Learn Kafka and integrate it with Spark
Learn troubleshooting techniques and performance improvement tips

This is complete end-to-end implementation course and we are very proud to bring this course to you.

Enroll now at this promotional fee and join the world of Big Data !

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What Will You Learn?

  • Understand the architecture of Hadoop
  • Understand file formats and the ability to choose the right format for a given use case
  • Develop applications on local system and then deploy them into production
  • Parameterize the code and make it production ready
  • Import data from mysql database into sqoop. Export data from hdfs to mysql. Get a deep understanding of sqoop
  • Query and analyze the data effectively using Hive.
  • Get a strong understanding of hive
  • Learn Scala - one of the top programming languages
  • Learn basic, intermediate and Advance concepts of Spark which is very hot in the market
  • Work with complex data and learn how to process them effectively
  • Learn Cassandra and integrate it with Spark
  • Learn HBase and integrate it with Spark
  • Learn Apache NIFI
  • Work with Spark Streaming - Learn about Kafka and how it integrates with Spark
  • Get a good understanding of end to end big data pipeline

Course Content

Introduction to the Big Data World
What this course is about How to make the best use of this course PPT and Pdf notes

  • Introduction to Hadoop
    00:00
  • How Map Reduce works
    00:00
  • Hadoop 1.0 Architecture
    00:00
  • Hadoop 2.0 Architecture
    00:00
  • Hadoop 3.0 Architecture
    00:00

Setting up cluster and doing hands on with Hadoop
Cloudera Software Installation [Notes] Cloudera Software Installation Hadoop Commands [Notes] Hadoop Commands Row Storage vs Column Storage Serialized File Formats [Notes] Serialized File Formats Hadoop and Big Data Interview questions and Answers

Setting up cluster and doing hands on with Hadoop

Sqoop

Hive

Installation for Spark and Scala

Learn Scala

Introduction to Spark

Spark RDDs

Spark Data Frames

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