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Perform data science with Azure Databricks · LearnSpace
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Perform data science with Azure Databricks

Курс от Microsoft
Средний≈ 25.9 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

In this course, you will learn how to harness the power of Apache Spark and powerful clusters running on the Azure Databricks platform to run data science workloads in the cloud. This is the fourth course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azurec ertification exam. The certification exam is an opportunity to prove knowledge and expertise operate machine learning solutions at a cloud-scale using Azure Machine Learning. This specialization teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Each course teaches you the concepts and skills that are measured by the exam. This Specialization is intended for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. It teaches data scientists how to create end-to-end solutions in Microsoft Azure. Students will learn how to manage Azure resources for machine learning; run experiments and train models; deploy and operationalize machine learning solutions, and implement responsible machine learning. They will also learn to use Azure Databricks to explore, prepare, and model data; and integrate Databricks machine learning processes with Azure Machine Learning.

Навыки, которые вы освоите

DatabricksApache SparkPySparkDistributed ComputingBig DataModel DeploymentMachine Learning MethodsExploratory Data AnalysisData ManipulationMicrosoft AzureData LakesData ProcessingMLOps (Machine Learning Operations)Data PipelinesModel EvaluationDeep LearningModel TrainingMachine LearningData Transformation

Программа курса

6 модулей · 105 учебных материалов

01Introduction to Azure Databricks17 материалов

Welcome to the Course

Introduction to the courseВидеоCourse syllabusЧтениеHow to be successful in this courseЧтениеMeet and greetОбсуждение

Учитесь у экспертов

Microsoft

Преподаватель курса

Perform data science with Azure Databricks
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Обучение на Coursera

≈ 25.9 ч

6 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Украинский, Китайский (Китай), Греческий, Итальянский, Бразильский португальский, Вьетнамский, Нидерландский, Корейский, Немецкий, Пушту, Русский, Тайский, Индонезийский, Шведский, Турецкий, Испанский, Дари, Хинди, Японский, Казахский, Польский

Часть программы вашего университета

Describe Azure Databricks

Explain Azure DatabricksВидео
Create an Azure Databricks workspace and clusterЧтение
Create and execute a notebookЧтение
Exercise: Work with NotebooksЧтение
Exercise quizЗадание
Knowledge checkЗадание
Lesson summaryВидео

Spark architecture fundamentals

Lesson introductionВидеоUnderstand the architecture of Azure Databricks Spark clusterВидеоUnderstand the architecture of spark jobВидеоKnowledge checkЗаданиеTest prepЗаданиеLesson summaryВидео
02Working with data in Azure Databricks18 материалов

Use Azure Databricks to prepare the data for advanced analytics and machine learning operations

Lesson introductionВидеоRead data in CSV formatЧтениеRead data in JSON formatЧтениеRead data in Parquet formatЧтениеRead data stored in tables and viewsЧтениеWrite dataЧтениеExercises: Read and write dataЧтениеExercise quizЗаданиеKnowledge checkЗаданиеLesson summaryВидео

Work with DataFrames in Azure Databricks

Lesson introductionВидеоDescribe a DataFrameЧтениеUse common DataFrame methodsЧтениеUse the display functionЧтениеExercise: Distinct articlesЧтениеKnowledge checkЗаданиеTest prep
03Processing data in Azure Databricks17 материалов

Build and query a Delta Lake

Describe the open source Delta LakeВидеоGet started with Delta using Spark APIsЧтениеExercise: Work with basic Delta Lake functionalityЧтениеExercise quizЗаданиеDescribe how Azure Databricks manages Delta LakeЧтениеExercise: Use the Delta Lake Time Machine and perform optimizationЧтениеExercise quizЗаданиеKnowledge checkЗаданиеLesson summaryВидео

Work with user-defined functions

Lesson introductionВидеоWrite user defined functionsЧтениеExercise: Perform Extract, Transform, Load (ETL) operations using user-defined functionsЧтениеExercise quizЗаданиеKnowledge checkЗаданиеTest prepЗадание
04Get started with Databricks and machine learning23 материалов

Perform machine learning with Azure Databricks

Lesson introductionВидеоUnderstand machine learningЧтениеExercise: Train a model and create predictionsЧтениеExercise quizЗаданиеUnderstand data using exploratory data analysisЧтениеExercise: Perform exploratory data analysisЧтениеExercise QuizЗаданиеDescribe machine learning workflowsЧтениеExercise: Build and evaluate a baseline machine learning modelЧтениеExercise quizЗаданиеKnowledge checkЗаданиеLesson summaryВидео

Train a machine learning model

Lesson introductionВидеоPerform featurization of the datasetЧтениеExercise: Finish featurization of the datasetЧтениеExercise quiz ЗаданиеUnderstand regression modelingЧтениеExercise: Build and interpret a regression modelЧтение
05Manage machine learning lifecycles and fine tune models14 материалов

Work with MLflow in Azure Databricks

Lesson introductionВидеоUse MLflow to track experiments, log metrics, and compare runsЧтениеExercise: Work with MLflow to track experiment metrics, parameters, artifacts and modelssЧтениеExercsie quizЗаданиеKnowledge checkЗаданиеLesson summaryВидео

Perform model selection with hyperparameter tuning

Lesson introductionВидеоDescribe model selection and hyperparameter tuningЧтениеExercise: Select optimal model by tuning hyperparametersЧтениеExercsie quizЗаданиеKnowledge checkЗаданиеTest prepЗадание
06Train a distributed neural network and serve models with Azure Machine Learning16 материалов

Deep learning with Horovod for distributed training

Lesson introductionВидеоUse Horovod to train a deep learning modelЧтениеUse Petastorm to read in Apache Parquet format with Horovod for distributed model trainingЧтениеExercise: Work with Horovod and Petastorm for training a deep learning modelЧтениеExercsie quizЗаданиеKnowledge checkЗаданиеLesson summaryВидео

Work with Azure Machine Learning to deploy serving models

Lesson introductionВидеоUse Azure Machine Learning to deploy serving modelsЧтениеKnowledge checkЗаданиеTest prepЗаданиеLesson summaryВидеоAdditional resourcesЧтение

Course wrap up

CongratulationsВидеоReflect on learningОбсуждениеNext stepsЧтение
Задание
Lesson summaryВидео
Lesson summaryВидео
Additional resourcesЧтение
Exercise quiz Задание
Knowledge checkЗадание
Test prepЗадание
Lesson summaryВидео
Additional resourcesЧтение
Lesson summaryВидео
Additional resourcesЧтение