The Big Data Certification Training Bundle

The Big Data Certification Training Bundle


The Big Data Certification Training Bundle:

Learn By Example: Hadoop & MapReduce for Big Data Problems

Discover Mass Data Processing Methods by Using the Leading Data Frameworks

By Loonycorn


Isn’t Big Data a little intimidating? This course, on the other hand, seeks to make things a lot easier for you. You’ll learn how to efficiently analyze and manage massive volumes of data with Hadoop and MapReduce. Anyone interested in data science should take this course since any organization that collects large volumes of data, from startups to Fortune 500 companies, needs employees who are fluent in Hadoop and MapReduce.

24/7 access to 71 lectures and 13 hours of content

  • Create your own Hadoop cluster with the help of virtual machines (VMs) and the cloud.
  • Understand HDFS, MapReduce, and YARN, as well as how they interact.
  • To recommend friends in a social network, develop search engines, and generate bigrams, use MapReduce.
  • Chain multiple MapReduce jobs together
  • Write your own customized partitioner
  • By sampling input files, you can learn how to sort a vast amount of data globally.


From 0 to 1 : Spark for Data Science in Python course

Make Your Data Fly Using Spark for Analytics, Machine Learning, & Data Science

By Loonycorn


To properly manage large amounts of data, analysts and data scientists usually have to deal with numerous systems. Spark, on the other hand, is a single engine that allows you to explore and work with enormous volumes of data, execute machine learning algorithms, and conduct a variety of other tasks all in one interactive environment. This course is ideal for anyone interested in working in the profitable and rapidly increasing sector of Big Data since it focuses on new and innovative technologies in data science and machine learning.

  • 24 hours a day, 7 days a week, you can access 52 lectures and 8 hours of content.
  • Spark may be used for a wide range of analytics and machine learning activities.
  • Complicated algorithms, such as PageRank and Music Recommendations, should be implemented.
  • Work with a wide range of datasets, including airline delays, Twitter, site graphs, and product ratings.
  • Use all of Spark’s capabilities and libraries, including RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming, and GraphX.


Scalable Programming with Scala & Spark

Get Rich Using Scala & Spark for Data Analysis, Machine Learning & Analytics

By Loonycorn


Scala is particularly well suited for a distributed computing framework like Spark due to its functional programming style and the availability of a REPL environment. Combining these two technologies can help you examine and explore data in an interactive environment with lightning-fast feedback. This course will show you how to mix Spark with Scala in the most effective way possible, making it ideal for aspiring data analysts and Big Data developers.


  • 24/7 access to 51 lectures and 8.5 hours of content.
  • Spark may be used for a wide variety of analytics and machine learning activities.
  • Recognize Scala’s functional programming constructs
  • Utilize sophisticated algorithms such as PageRank and Music Recommendations.
  • Work with a range of datasets, including airplane delays, Twitter, site graphs, and product ratings.
  • Utilize Spark’s various capabilities and libraries, including RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming, and GraphX.
  • Write code in Scala REPL environments and use an IDE to build Scala applications.


Learn by Example: HBase – The Hadoop Database

Create More Flexible Databases by Mastering HBase

By Loonycorn

HBase is an incredibly effective databasing solution for organizing and managing enormous data sets for Big Data engineers and data analysts. HBase provides improved flexibility by allowing column-oriented storage, no fixed schema, and low latency to satisfy applications’ constantly changing demands. With the 25 examples in this course, you’ll gain a thorough understanding of HBase, which you may use in interviews for Big Data employment.

  • 24/7 access to 41 lectures and 4.5 hours of content
  • Create an HBase database for your application.
  • For data processing jobs, combine HBase and MapReduce.
  • HBase can be used to create tables, insert data, read data, and delete data.
  • Learn everything there is to know about HBase and its place in the Hadoop ecosystem.
  • Investigate CRUD operations using the shell and the Java API.


Introduction to Computer Networks for Non-Techies

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