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Databricks Associate Developer: Apache Spark with Python · LearnSpace
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Databricks Associate Developer: Apache Spark with Python

Курс от Packt
Средний≈ 19.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

This course equips you with essential skills for working with Apache Spark using Python, preparing you for Databricks' certification exam. Apache Spark is a powerful open-source engine for processing large-scale data, and mastering it is a key asset in the data engineering and big data domain. Throughout the course, learners will gain hands-on experience with Spark's core components, including data processing, streaming, and machine learning. Practical examples and exercises will build confidence and ensure you're ready for real-world challenges. What sets this course apart is its strong focus on practical skills and real-world applications of Apache Spark. You'll not only learn the theory but also apply your knowledge in hands-on projects that reinforce the concepts. This course is ideal for aspiring data engineers, analysts, or scientists who want to achieve Databricks certification. A solid understanding of Python is required, and familiarity with Pyspark is beneficial, but not mandatory.

Навыки, которые вы освоите

Apache SparkApplied Machine LearningDistributed ComputingBig DataData ManipulationMachine LearningData ProcessingReal Time DataModel EvaluationSQLPython ProgrammingPySparkPerformance TuningApacheData TransformationDatabricks

Программа курса

8 модулей · 68 учебных материалов

01Overview of the Certification Guide and Exam4 материалов

Lesson 1

Introduction - Overview VideoВидеоOverview of the Certification Guide and Exam - Overview VideoВидеоOverview of the Certification Guide and Exam - The ReadingЧтениеCertification Exam Preparation Guide

Учитесь у экспертов

Packt - Course Instructors

Преподаватель курса

Databricks Associate Developer: Apache Spark with Python
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Обучение на Coursera

≈ 19.9 ч

8 модулей

Язык: Английский

Часть программы вашего университета
Задание
02Understanding Apache Spark and Its Applications10 материалов

Lesson 1

Understanding Apache Spark and Its Applications - Overview VideoВидеоIntroductionЧтениеSpark CoreЧтениеSpark MLlibЧтениеPractice: Map Spark Components to a Real-World ScenarioDIALOGUEBig Data ProcessingЧтениеReal-time StreamingЧтениеData EngineersЧтениеData ScientistsЧтениеExploring Apache Spark FundamentalsЗадание
03Spark Architecture and Transformations7 материалов

Lesson 1

Spark Architecture and Transformations - Overview VideoВидеоIntroductionЧтениеCluster ManagerЧтениеPractice: Analyze a Spark Performance ProblemDIALOGUEPartitioning in SparkЧтениеNarrow TransformationsЧтениеSpark Fundamentals and Execution ModelЗадание
04Spark DataFrames and Their Operations8 материалов

Lesson 1

Spark DataFrames and Their Operations - Overview VideoВидеоIntroductionЧтениеViewing Columns of DataЧтениеConverting a PySpark DataFrame to a Pandas DataFrameЧтениеPractice: Decide When to Use PySpark vs. PandasDIALOGUEChanging the Case of a ColumnЧтениеDropping Null Values from a DataFrameЧтениеSpark DataFrame FundamentalsЗадание
05Advanced Operations and Optimizations in Spark13 материалов

Lesson 1

Advanced Operations and Optimizations in Spark - Overview VideoВидеоIntroductionЧтениеJoining DataFrames in SparkЧтениеUse caseЧтениеReading and Writing DataЧтениеReading and Writing Delta FilesЧтениеPractice: Optimize a Spark Data PipelineDIALOGUECatalyst OptimizerЧтениеData-based Optimizations in Apache SparkЧтениеManaging Data Spills in Apache SparkЧтениеShuffle JoinsЧтениеOptimizing Wide TransformationsЧтениеMastering Spark Execution and Data ManagementЗадание
06SQL Queries in Spark7 материалов

Lesson 1

SQL Queries in Spark - Overview VideoВидеоIntroductionЧтениеLoading and Saving DataЧтениеSortingЧтениеPractice: Design a Spark SQL Reporting StrategyDIALOGUECalculating Cumulative Sum Using Window FunctionsЧтениеMastering Spark SQL QueriesЗадание
07Structured Streaming in Spark7 материалов

Lesson 1

Structured Streaming in Spark - Overview VideoВидеоIntroductionЧтениеIntroducing Structured StreamingЧтениеPractice: Design for Late Data in Structured StreamingDIALOGUEEvent Time and Processing TimeЧтениеStreaming Sources and SinksЧтениеStructured Streaming FundamentalsЗадание
08Machine Learning with Spark ML12 материалов

Lesson 1

IntroductionЧтениеUnsupervised LearningЧтениеML with SparkЧтениеSpark MLlibЧтениеML Life CycleЧтениеPractice: Design a Spark ML Project PlanDIALOGUEHandling Categorical VariablesЧтениеAssembling the VectorЧтениеCross-validationЧтениеModel Monitoring and ManagementЧтениеModel Iteration and ImprovementЧтениеMachine Learning with Spark MLЗадание