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所在平台: Udemy |
课程主页: https://www.udemy.com/course/databricks-certified-associate-developer-for-apache-spark-o/
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课程名称：Databricks认证助理开发者（Apache Spark） 课程概述： 本课程旨在为希望获得Databricks认证的学习者提供全面的实操培训，帮助他们为Databricks认证助理开发者（Apache Spark）考试做好准备。在以数据为驱动的现代世界中，Apache Spark已成为标准的大数据集群处理框架，而Databricks已成为大数据的参考工具。拥有这一认证，将有助于在大数据就业市场中占据有利地位。 本课程包含理论培训、可下载的学习指南、实操练习和模拟考试，是学习Apache Spark及获得认证所需的唯一课程。考试包含60道选择题，考生需在120分钟内完成。 课程涵盖的主题包括： 1. 认证准备：学习如何有效准备Databricks考试，包含策略和技巧，以及每个部分的实践讲座和模拟测试。 2. Spark架构 - 概念：包括集群架构、Spark执行层次结构、数据分区、懒计算、转换与动作的区别等。 3. Spark架构 - 应用：执行部署模式、稳定性、存储级别、数据重分区、广播等。 4. Spark DataFrame API：如何对DataFrame进行子集选择、列操作、字符串处理、性能优化操作、联合DataFrame、读写DataFrame等。 5. 综合练习：提供一套完整的高质量练习题，以帮助考生为Databricks Certified Developer for Apache Spark 3.0考试做准备，题目涵盖Python和Apache Spark 3.0的所有考点。 通过参加本课程，提升自己的技能，加强职业机会，成为大数据专家。学员将获得终身访问权，包括PDF电子书、可下载的Spark项目文件、实际练习、测验和模拟考试、支持材料及专家一对一指导等资源。 准备好提升自己的技能并迈出职业生涯的新步伐吗？欢迎加入我们！
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!
