Udemy - JMeter - Step by Step for Beginners [Free]

Udemy - JMeter - Step by Step for Beginners 

Udemy - JMeter - Step by Step for Beginners
Free

  • Lectures 25
  • Length 5 hours
  • Skill Levels All Levels
  • Languages English
  • Published 4/2018

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Description

In this course we will learn Jmeter from scratch step by step.
We will learn the basics in a very easy way and you will be able to use JMeter for all types of performance and functional testing.
After this course you can work with JMeter for personal and enterprise projects.
LET'S GET STARTED...

 

Udemy - Getting Started with BlazeMeter [Free]

Udemy - Getting Started with BlazeMeter 

Udemy - Getting Started with BlazeMeter
Free

  • Lectures 37
  • Length 3 hours
  • Skill Levels All Levels
  • Languages English
  • Published 4/2018

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Description

This course contains all the information you need to know about getting started with BlazeMeter and Apache JMeter™. You will learn the basics of these products and quickly start developing and running your own tests. You will also see some key videos and have an opportunity to perform some hands-on lab exercises. 

Udemy - Apache Spark with Python - Big Data with PySpark and Spark [Free]

Udemy - Apache Spark with Python - Big Data with PySpark and Spark 

Udemy - Apache Spark with Python - Big Data with PySpark and Spark
Free

  • Lectures 48
  • Length 3.5 hours
  • Skill Levels All Levels
  • Languages English
  • Published 2/2018

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Description

What is this course about:
This course covers all the fundamentals about Apache Spark with Python and teaches you everything you need to know about developing Spark applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipeline and data analytics applications.
This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom.  And much much more.
What will you learn from this lecture:
In particularly, you will learn:
  • An overview of the architecture of Apache Spark.
  • Develop Apache Spark 2.0 applications with PySpark using RDD transformations and actions and Spark SQL.
  • Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.
  • Deep dive into advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.
  • Scale up Spark applications on a Hadoop YARN cluster through Amazon's Elastic MapReduce service.
  • Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Spark SQL.
  • Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators.
  • Best practices of working with Apache Spark in the field.
  • Big data ecosystem overview.

Why should you learn Apache Spark:
Apache Spark gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world.
Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks.
Apache Spark is the next-generation processing engine for big data.
Tons of companies are adapting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop.
Apache Spark is becoming a must tool for big data engineers and data scientists.
What programming language is this course taught in?
This course is taught in Python. Python is currently one of the most popular programming languages in the world! It's rich data community, offering vast amounts of toolkits and features makes it a powerful tool for data processing. Using PySpark (the Python API for Spark) you will be able to interact with Apache Spark's main abstraction, RDDs, as well as other Spark components, such as Spark SQL and much more!
Let's learn how to write Spark programs with PySpark to model big data problems today!
30-day Money-back Guarantee!
You will get 30-day money-back guarantee from Udemy for this course.
If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked.
Are you ready to take your big data analysis skills and career to the next level, take this course now!
You will go from zero to Spark hero in 4 hours.

 

Udemy - Apache Spark with Python - The next generation of Big Data [Free]

Udemy - Apache Spark with Python - The next generation of Big Data 

Udemy - Apache Spark with Python - The next generation of Big Data
Free

  • Lectures 12
  • Length 1 hour
  • Skill Levels All Levels
  • Languages English
  • Published 4/2017

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Description

Anyone who wants to gather perspective on Apache Spark as a technology for free is an appropriate audience. Struggling with understanding the basic big data concepts although people are using the keywords anytime they can? Catch up to them and learn the big data concepts the right way! 
Join the teaser apache spark course which consists of what Apache Spark is and a live demo of things up and running integrated with Twitter!

 

Udemy - Apache Sqoop for Certifications - CCA and HDPCD [Free]

Udemy - Apache Sqoop for Certifications - CCA and HDPCD 

Udemy - Apache Sqoop for Certifications - CCA and HDPCD
Free

  • Lectures 32
  • Length 6.5 hours
  • Skill Levels All Levels
  • Languages English
  • Published 11/2017

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Description

As part of this course, we will be
  • Seeing various setup options to explore sqoop
  • Understand how to import data from mysql database to Hadoop HDFS/Hive
  • All the important control arguments while performing import
  • Export data from Hive/HDFS to MySQL
After the course, you can confidently execute scenarios related to sqoop as part of certifications and also make better decisions while building data integration frameworks using Sqoop.

 

Udemy - Apache Spark with Scala - Mastering Big Data! [Free]

Udemy - Apache Spark with Scala - Mastering Big Data! 

Udemy - Apache Spark with Scala - Mastering Big Data!
Free

  • Lectures 42
  • Length 2.5 hours
  • Skill Levels Beginner Levels
  • Languages English
  • Published 10/2017

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Description

Udemy - Learn Apache Maven [Free]

Udemy - Learn Apache Maven 

Udemy - Learn Apache Maven
Free

  • Lectures 22
  • Length 1 hour
  • Skill Levels All Levels
  • Languages English
  • Published 9/2017

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Description

This course is designed to help you understand the core concepts of Maven and get you started on writing build automation scripts independently using it.
In this course, you will learn what is Maven and its core features.
You start with installation and learn to make some customizations to it.
Then you create a simple hello world java project automatically using Maven commands and with the help of this simple project you would learn various things that make Maven the de-facto standard that it is today.
You will also learn to create a webapp automatically, using maven commands, run code checks, run automated tests using JUnit and finally deploy to a web server - all using Maven.
You would get a good understanding of how to write your own maven build using some very frequently used plugins and dependencies.
You will learn about using Maven for multi module projects that you would see more often in real projects.
You will also learn how to auto-generate great documentation for your project using maven site lifecycle.
To top it off, you would be learning all these concepts and implementing them on Eclipse IDE that is free, open source and easy to use.
 The theory is kept crisp and is always accompanied with hands on in order to make the course more engaging.

 

Udemy - Apache Spark Course with Java [Free]

Udemy - Apache Spark Course with Java 

Udemy - Apache Spark Course with Java
Free

  • Lectures 46
  • Length 3.5 hours
  • Skill Levels Beginner Level
  • Languages English
  • Published 8/2017

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Description

What is this course about:
This course covers all the fundamentals about Apache Spark and teaches you everything you need to know about developing Spark applications. At the end of this course, you will gain in-depth knowledge about Apache Spark and general big data analysis and manipulations skills to help your company to adapt Apache Spark for building big data processing pipeline and data analytics applications.
This course covers 10+ hands-on big data examples. You will learn valuable knowledge about how to frame data analysis problems as Spark problems. Together we will learn examples such as aggregating NASA Apache web logs from different sources; we will explore the price trend by looking at the real estate data in California; we will write Spark applications to find out the median salary of developers in different countries through the Stack Overflow survey data; we will develop a system to analyze how maker spaces are distributed across different regions in the United Kingdom.  And much much more.
What will you learn from this lecture:
In particularly, you will learn:
  • An overview of the architecture of Apache Spark.
  • Develop Apache Spark 2.0 applications using RDD transformations and actions and Spark SQL.
  • Work with Apache Spark's primary abstraction, resilient distributed datasets(RDDs) to process and analyze large data sets.
  • Deep dive into advanced techniques to optimize and tune Apache Spark jobs by partitioning, caching and persisting RDDs.
  • Scale up Spark applications on a Hadoop YARN cluster through Amazon's Elastic MapReduce service.
  • Analyze structured and semi-structured data using Datasets and DataFrames, and develop a thorough understanding of Spark SQL.
  • Share information across different nodes on an Apache Spark cluster by broadcast variables and accumulators.
  • Best practices of working with Apache Spark in the field.
  • Big data ecosystem overview.
Why shall we learn Apache Spark:
Apache Spark gives us unlimited ability to build cutting-edge applications. It is also one of the most compelling technologies of the last decade in terms of its disruption to the big data world.
Spark provides in-memory cluster computing which greatly boosts the speed of iterative algorithms and interactive data mining tasks.
Apache Spark is the next-generation processing engine for big data.
Tons of companies are adapting Apache Spark to extract meaning from massive data sets, today you have access to that same big data technology right on your desktop.
Apache Spark is becoming a must tool for big data engineers and data scientists.
About the author:
Since 2015, James has been helping his company to adapt Apache Spark for building their big data processing pipeline and data analytics applications.
James' company has gained massive benefits by adapting Apache Spark in production. In this course, he is going to share with you his years of knowledge and best practices of working with Spark in the real field.
Why choosing this course?
This course is very hands-on, James has put lots effort to provide you with not only the theory but also real-life examples of developing Spark applications that you can try out on your own laptop.
James has uploaded all the source code to Github and you will be able to follow along with either Windows, MAC OS or Linux.
In the end of this course, James is confident that you will gain in-depth knowledge about Spark and general big data analysis and data manipulation skills. You'll be able to develop Spark application that analyzes Gigabytes scale of data both on your laptop, and in the cloud using Amazon's Elastic MapReduce service!
30-day Money-back Guarantee!
You will get 30-day money-back guarantee from Udemy for this course.
 If not satisfied simply ask for a refund within 30 days. You will get a full refund. No questions whatsoever asked.
Are you ready to take your big data analysis skills and career to the next level, take this course now!
You will go from zero to Spark hero in 4 hours.

 

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