Apache Spark for Data Engineers

Data Storage, Integration, Processing and everything in between a data egineer need to know.

Join the most comprehensive Apache Spark Hands-on Course, because now is the time to get started!

What you’ll learn

  • Hadoop.
  • Spark.
  • Spark Data Frame, PySpark, Spark SQL, Machine Learning.
  • Databricks.
  • Python.
  • Spark Partition.
  • Spark Transformation & Shuffle.
  • Databricks Connect.

Course Content

  • Introduction –> 1 lecture • 4min.
  • Big Data Fundamentals –> 5 lectures • 38min.
  • Spark Basics –> 2 lectures • 11min.
  • PySpark –> 3 lectures • 23min.
  • Databricks –> 7 lectures • 53min.
  • Spark: Advanced Concepts –> 4 lectures • 11min.
  • Databricks Connect –> 8 lectures • 36min.
  • Conclusion –> 1 lecture • 1min.

Apache Spark for Data Engineers

Requirements

  • Should be able to work on computer.
  • Basic knowledge of Python would be beneficial.

Join the most comprehensive Apache Spark Hands-on Course, because now is the time to get started!

From basic concepts about Big data and Spark to PySpark, Spark SQL, Databricks, submitting a live application on Spark cluster, this course covers all you need to know to become a successful Spark Data Engineer!

But that’s not all! Along with covering all the steps of Spark Data Engineering functions, this course will also have quizzes and projects, which allow you to practice the things learned throughout the course!

You’ll not only learn about the concepts but also practice each of those concepts through hands-on and real-life Projects.

And if you do get stuck, you benefit from extremely fast and friendly support – both via direct messaging or discussion. You have my word!

With more than two decades of IT experience, I have designed this course for students and professionals who wish to master industry-standard Spark Data Engineering projects.

This course will be kept up-to-date to ensure you don’t miss out on any changes once Spark is required in your project!

Why Data Engineering & Spark?

In current times, Data Engineering is among the most popular career choices. Data Engineering and Machine Learning are among the best jobs of 2019 with a 344% average growth in Salary.

The following features of Spark make it the most desirable data engineering tool:

  • Compatibility with Hadoop
  • At least 100 times faster than Hadoop MapReduce
  • Highly diverse nature of Spark with APIs available in Python, Java, SQL, and R
  • Spark is the only software framework that combines data and AI. Using Spark one can do large-scale data transformation and analysis and then immediately run AI and Machine learning algorithms on it.
  • Build-in unified analytics platform by the cloud providers like Databricks

If you are looking for a thriving career in Data Engineering, this is the right time to learn Spark. Knowledge of Spark will open up a lot of opportunities.

That provides hands-on working experience and also helps to learn through hands-on projects.

Don’t be left out and prepare well for these opportunities.

So, what are you waiting for?

Pay once, benefit a lifetime!

This is an evolving course! Spark and future enhancements will be covered in this course. You won’t lose out on anything! Don’t lose any time, gain an edge, and start now!