What you'll learn
How to prepare for the Databricks Certified Associate Developer For Apache Spark 3 Certification Exam
Learn how Apache Spark runs on a cluster of computer
Learn the different techniques to select the columns of a DataFrame
How to use Databricks Community Edition to write Apache Spark Code
Understanding the basics of the Spark architecture, including Adaptive Query Execution
Apply the Spark DataFrame API to complete individual data manipulation task
Requirements
Python fundamentals
Description
If you are looking for a certification-oriented, hands-on and comprehensive course to prepare for the Databricks Certified Associate Developer for Apache Spark certification, you have come to the right place.This course is designed to prepare you to learn everything related to the Databricks Certified Associate Developer for Apache Spark certification.In today's data-driven world, Apache Spark has become the standard big-data cluster processing framework. And Databricks have become the reference tool for Big Data. For this reason, Databricks is one of the most valuable skills today. Having the Databricks Certified Associate Developer for Apache Spark certification will allow you to position yourself in the Big Data job market. Get certified and advance your Big Data career.With theoretical training, downloadable study guides, hands-on exercises, and mock exams, this is the only course you'll need to learn Apache Spark in Databricks and get certified. The exam consists of 60 multiple-choice questions. Candidates will have 120 minutes to complete the exam.Topics covered in the course:Certification preparation. This course teaches you how to prepare for the Databricks exam. Including tips, proved preparation methodology, hands-on lectures in every section and tips and strategies using Mock Test.Spark Architecture - Conceptual· Cluster architecture: nodes, drivers, workers, executors, slots, etc.· Spark execution hierarchy: applications, jobs, stages, tasks, etc.· Shuffling· Partitioning· Lazy evaluation· Transformations vs Actions· Narrow vs Wide transformationsSpark Architecture - Applied· Execution deployment modes· Stability· Storage levels· Repartitioning· Coalescing· Broadcasting· DataFramesSpark DataFrame API· Subsetting DataFrames (select, filter, etc.)· Column manipulation (casting, creating columns, manipulating existing columns, complex column types)· String manipulation (Splitting strings, regex)· Performance-based operations (repartitioning, shuffle partitions, caching)· Combining DataFrames (joins, broadcasting, unions, etc)· Reading/writing DataFrames (schemas, overwriting)· Working with dates (extraction, formatting, etc)· Aggregations· Miscellaneous (sorting, missing values, typed UDFs, value extraction, sampling)Finally, we will conclude with a complete, comprehensive set of realistic, high-quality questions to practice for the Databricks Certified Developer for Apache Spark 3.0 exam in Python. These up-to-date practice exams provide you with the knowledge and confidence you need to pass the exam with excellence. Questions are based on the actual distribution of topics in the real exam. We include also real exam questions.The questions cover all themes being tested for in the exam, including specifics to Python and Apache Spark 3.0.If you're ready to sharpen your skills, increase your career opportunities, and become a Big Data expert, join today and get immediate and lifetime access to:• Complete guide to Databricks Certified Associate Developer for Apache Spark guide (PDF e-book)• Downloadable Spark project files• Practical exercises•Quizzes and mock exams• Spark resources like Cheatsheets and Summaries• 1 to 1 expert support• Course question and answer forumSee you there!
Who this course is for
Any Developer who wants to start using Apache Spark in their career
Beginner Spark Developer seeking Big Data Certification
Anyone that want to pass Databricks Certified Associate Developer for Apache Spark in the first attempt

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rapidgator.net:

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