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Azure Databricks Master Program [real time scenarios + Labs]

SynopsisAzure Databricks Master Program [real time scenarios + Labs],...
Azure Databricks Master Program [real time scenarios + Labs]  No.1

Azure Databricks Master Program [real time scenarios + Labs], available at $54.99, has an average rating of 3.75, with 15 lectures, based on 14 reviews, and has 124 subscribers.

You will learn about Implementing Architecture for big data analytics projects using databricks Deep knowledge on Azure Databricks Internal Architecture Internals of Spark Architecture and How Execution Engine works Creating data pipelines in databricks Transforming data using Spark core and Spark SQL This course is ideal for individuals who are University Students or Software Engineers or Architects It is particularly useful for University Students or Software Engineers or Architects.

Enroll now: Azure Databricks Master Program [real time scenarios + Labs]

Summary

Title: Azure Databricks Master Program [real time scenarios + Labs]

Price: $54.99

Average Rating: 3.75

Number of Lectures: 15

Number of Published Lectures: 13

Number of Curriculum Items: 15

Number of Published Curriculum Objects: 13

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

  • Implementing Architecture for big data analytics projects using databricks
  • Deep knowledge on Azure Databricks Internal Architecture
  • Internals of Spark Architecture and How Execution Engine works
  • Creating data pipelines in databricks
  • Transforming data using Spark core and Spark SQL
  • Who Should Attend

  • University Students
  • Software Engineers
  • Architects
  • Target Audiences

  • University Students
  • Software Engineers
  • Architects
  • What is Azure Databricks

    Challenges to solutions with Azure Databricks

    History of Azure Databricks

    Azure Databricks Architecture

    Azure Databricks Data Flow Architecture

    Batch Data Processing with Azure Databricks

    Stream Data Processing with Azure Databricks

    Machine Learning on batch data with Azure Databricks

    Interface

    Workspace

    Data Management

    Computation Management

    Model Management

    Authentication and Authorization

    How to login  into azure portal

    How to create Azure Databricks

    Dashboard

    Home

    Workspace

    Recent

    Data Management

    Computation Management

    Model Management

    Job Management

    Search

    Creating and configuring clusters in Azure Databricks

    How to create Python notebook

    How to create Scala notebook

    How to create SQL notebook

    How to create R notebook

    How to login  into azure portal

    How to create Azure Databricks

    Creating and configuring clusters in Azure Databricks

    How to create notebook

    How to detach and attach notebook to another cluster

    How to Export Notebook in different formats

    How to Import Notebook from different formats

    How to clone Notebook

    How to move Notebook

    How to change default language of Notebook

    How to move cells

    How to create and delete cells

    How to use shortcuts to execute cells

    How to comment code in notebook

    All Options available on Notebook

    How to create new database in Azure Databricks

    How to describe database in Azure Databricks

    How to drop database in Azure Databricks

    How to drop Non empty database in Azure Databricks

    How to create table with UI

    How to create table with Notebook

    Difference between table with UI and table with notebook

    How to create table in specified database with UI

    How to create table in specified database with Notebook

    How to create empty table

    How to create Partition table with Notebook

    How to append or overwrite partitions in table

    How to describe table in Azure Databricks

    How to drop table in Azure Databricks

    How to upload data into Databricks File System

    Command to create directory in dbfs

    Command to create file and write data to it

    Command to display file content

    Command to list down content in a directory

    Command to move files from one directory to another directory

    Command to copy file from one directory to another directory

    Command to remove file and directories

    Command to mount and unmount file system

    Command to list down mount

    Command to refresh mount points

    Command to install the packages

    Command to find current notebook path/ from UI

    Command to run one notebook from another notebook

    Command to exit notebook execution

    Command to list down secret scopes

    What is widget and Types

    How to create widget to pass dynamic values to Python notebook

    How to read dynamic parameter values in Python notebook

    How to remove widget from python notebook

    How to create widget to pass dynamic values to Scala notebook

    How to read dynamic parameter values in  Scala notebook

    How to remove widget from scala notebook

    How to run notebook whenever we change the dynamic parameter values

    Widgets panel settings

    Prerequisites to install databricks cli

    How to install databricks cli

    How to authenticate to databricks workspace from cli

    How to create cluster

    How to terminate cluster

    How to start cluster

    How to restart cluster

    How to get list of clusters

    How to get list of notebook

    How to import notebook into databricks from local

    How to export notebook

    How to remove notebook

    How to create folders

    How to get list of folders in dbfs

    How to create folder in dbfs

    How to copy files from local to dbfs

    How to move file from one folder to another folder

    How to remove files from dbfs

    How to remove folders from dbfs

    How to install libraries

    How to uninstall libraries

    How to create job

    How to run job

    1. PySpark Read CSV file into DataFrame

    Read single file

    Read all CSV files in a directory

    2. Options while reading CSV file

    delimiter

    InferSchema

    header

    3. Read CSV files with a user-specified schema

    Course Curriculum

    Chapter 1: Introduction to Azure Databricks

    Lecture 1: Introduction to Databricks

    Lecture 2: Azure Databricks Architecture

    Lecture 3: Azure Databricks Main Concepts

    Chapter 2: Azure Databricks Account Creation

    Lecture 1: Azure Free Account and Free Subscription For Azure Databricks

    Lecture 2: How to Create Databricks Community __ Azure Databricks

    Chapter 3: Databricks Cluster Types and Notebook Options

    Lecture 1: Creating and configuring clusters in Azure Databricks

    Lecture 2: How to create Databricks Cluster, Notebook & quick tour on notebook options

    Chapter 4: Databricks Integration with Hive

    Lecture 1: Azure Databricks Databases and Hive Tables

    Chapter 5: Databricks Utilities and Notebook Parameters

    Lecture 1: dbutils commands on files, directories, notebooks and libraries

    Lecture 2: Databricks Variables, Widget Types, Databricks notebook parameters

    Chapter 6: Databricks CLI

    Lecture 1: Azure Databricks CLI Installation

    Lecture 2: Databricks CLI – DBFS, Libraries and Jobs

    Chapter 7: Reading and Writing CSV files in Databricks

    Lecture 1: Read CSV Files efficiently in spark __ Azure Databricks

    Instructors

  • Azure Databricks Master Program [real time scenarios + Labs]  No.2
    Mallaiah Somula
    enterprise data architect
  • Rating Distribution

  • 1 stars: 1 votes
  • 2 stars: 3 votes
  • 3 stars: 4 votes
  • 4 stars: 2 votes
  • 5 stars: 4 votes
  • Frequently Asked Questions

    How long do I have access to the course materials?

    You can view and review the lecture materials indefinitely, like an on-demand channel.

    Can I take my courses with me wherever I go?

    Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!