Spark Fundamentals II
Course
Spark Fundamentals II
Learn the fundamentals of Spark architecture. Discover how to test, and debug Spark applications using SBT, Eclipse, and IntelliJ.
Further your knowledge of this important tool and take an important step forward in your data science career.
Self-Paced
Mentored
Intermediate
Duration
2-3 hours/week
Apache Spark is a unified analytics engine utilized in big data analysis and machine learning. It is used to discover trends and real-time insights in many industries, including financial services, healthcare, manufacturing, and retail.
This course focuses on Apache Spark architecture.
You will explore input, partitioning, and parallelization. You will learn about optimization with respect to efficiently operating on and joining multiple datasets.
You will discover how Spark instructions are translated into jobs and what causes multiple stages within a job. You will explore Spark's memory caching for iterative processing. And you will learn about developing, testing, and debugging Spark applications using SBT, Eclipse, and IntelliJ.
Apache Spark is a popular general-purpose processor that is ideal for working with big data. If you are keen to build your experience through hands-on lab sessions, then this Spark Fundamentals course in an ideal step to take.
This course comprises five purposely designed modules that take you on a carefully defined learning journey.
It is a self-paced course, which does not run to a fixed schedule with regard to completing modules or submitting assignments. It is anticipated that if you work 2-3 hours per week, you will complete the course within 2 weeks. However, you can work at your own pace as long as the course is completed before the deadline.
The materials for each module are accessible from the start of the course and will remain available for the duration of your enrollment. Methods of learning and assessment will include reading material, hands-on labs and online exams questions.
As part of our mentoring service you will have access to valuable guidance and support throughout the course. We provide a dedicated discussion space where you can ask questions, chat with your peers, and resolve issues. Depending on the payment plan you have chosen, you may also have access to live classes and webinars, which are an excellent opportunity to discuss problems with your mentor and ask questions. Mentoring services may vary package wise.
Once you have successfully completed the course, you will earn your IBM Certificate.
After completing this course, you will:
- Have an understanding of Apache Spark architecture.
- Be able to perform input, partitioning, and parallelization.
- Be able to operate on and join multiple datasets.
- Be able to translate Spark operations into jobs.
- Be able to use Spark's memory caching for iterative processing.
- Be able to develop, test, and debug Spark applications using SBT, Eclipse, and IntelliJ.
- Individuals who need to understand data and data insights for their job.
- Individuals who aspire to become data scientists or data engineers.
- Apache Hadoop and big data.
- The Linux operating system.
- Scala, Python, R, or Java programming languages.