Would you like to advance your career and learning Apache Spark will help?
This course will help you get there and there’s no doubt Apache Spark is an in-demand skillset with higher pay.
This course prepares you for job interviews and technical conversations with hands-on exercises. At the end of this course, you can truthfully update your resume or CV with a variety of Apache Spark experiences.
How can this course help?
You will become confident and productive with Apache Spark after taking this course. You need to be confident and productive in Apache Spark to be more valuable.
Now, I’m not going to pretend here. You are going to need to put in work. This course puts you in a position to focus on the work you will need to complete.
This course uses Python, which is a fun, dynamic programming language perfect for both beginners and industry veterans.
At the end of this course, you will have rock-solid foundation to accelerate your career and growth in the exciting world of Apache Spark.
Why choose this course?
Let’s be honest. You can find Apache Spark learning material online for free. Using these free resources is okay for people with extra time.
This course saves you time and effort. It is organized in a step-by-step approach that builds upon each previous lessons.
The intended audience of this course is people who need to learn Spark in a focused, organized fashion.
All source code examples are available for download, so you can execute, experiment and customize for your environment after or during the course.
This Apache Spark with Python course covers over 50 hands-on examples. We run them locally first and then deploy them on cloud computing services such as Amazon EC2.
The following will be covered and more:
- What makes Spark a power tool of Big Data and Data Science?
- Learn the fundamentals of Spark including Resilient Distributed Datasets, Spark Actions, and Transformations
- Run Spark in a Cluster in your local environment and Amazon EC2
- Deploy Python applications to a Spark Cluster
- Explore Spark SQL with CSV, JSON and mySQL (JDBC) data sources
- Convenient links to download all source code
- Reinforce your understanding through multiple quizzes and lecture recap