Azure Cloud Azure Databricks Apache Spark Machine learning

Azure Cloud Azure Databricks Apache Spark Machine learning, available at $39.99, has an average rating of 2.15, with 75 lectures, based on 139 reviews, and has 766 subscribers.

You will learn about This course will provide you an in depth knowledge of apache Spark and how to work with spark using Azure Databricks You will understand the main concepts of Azure Cloud Youll learn about the basic use of Azure Cloud You will learn to deploy Apache Spark ecosystems locally Youll learn how to develop a databricks dependency library through IDEA You will be able to process continual streams of data with Spark streaming You will learn how to train a machine learning model You will understand the use case of graph analysis Deploy Azure Virtual Networks via the Portal Deploy Azure Resource Groups Youll learn how to use Azure Data Factory Youll learn the historical story of Apache Hadoop, Apache Spark and Graph Analysis Youll learn how to use Apche Zepplin to develop a hello world example of Spark Deploy Azure Virtual Networks via the Portal This course is ideal for individuals who are Anyone who wants to learn Spark, Machine Learning using Azure Databricks or Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer or Students who are willing to learn Azure from ground zero or Students who would like to make a career switch to Microsoft Azure cloud It is particularly useful for Anyone who wants to learn Spark, Machine Learning using Azure Databricks or Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer or Students who are willing to learn Azure from ground zero or Students who would like to make a career switch to Microsoft Azure cloud.

Enroll now: Azure Cloud Azure Databricks Apache Spark Machine learning

Summary

Title: Azure Cloud Azure Databricks Apache Spark Machine learning

Price: $39.99

Average Rating: 2.15

Number of Lectures: 75

Number of Published Lectures: 74

Number of Curriculum Items: 75

Number of Published Curriculum Objects: 74

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

This course will provide you an in depth knowledge of apache Spark and how to work with spark using Azure Databricks

You will understand the main concepts of Azure Cloud

Youll learn about the basic use of Azure Cloud

You will learn to deploy Apache Spark ecosystems locally

Youll learn how to develop a databricks dependency library through IDEA

You will be able to process continual streams of data with Spark streaming

You will learn how to train a machine learning model

You will understand the use case of graph analysis

Deploy Azure Virtual Networks via the Portal

Deploy Azure Resource Groups

Youll learn how to use Azure Data Factory

Youll learn the historical story of Apache Hadoop, Apache Spark and Graph Analysis

Youll learn how to use Apche Zepplin to develop a hello world example of Spark

Deploy Azure Virtual Networks via the Portal

Who Should Attend

Anyone who wants to learn Spark, Machine Learning using Azure Databricks

Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer

Students who are willing to learn Azure from ground zero

Students who would like to make a career switch to Microsoft Azure cloud

Target Audiences

Anyone who wants to learn Spark, Machine Learning using Azure Databricks

Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer

Students who are willing to learn Azure from ground zero

Students who would like to make a career switch to Microsoft Azure cloud

Microsoft Azure is the fastest growing cloud platform in the world. No prior Azure experience required.

Azure Databricks is unique collaboration between Microsoft and Databricks, forged to deliver Databricks’ Apache Spark-based analytics offering to the Microsoft Azure cloud. With Azure Databricks, you can be developing your first solution within minutes. Azure Databricks is a fast, easy and collaborative Apache Spark–based analytics service.

Databricks builds on top of Spark and adds:

?? ? Highly reliable and performant data pipelines

?? ? Productive data science at scale

In this course, you’ll have a strong understanding of azure databricks, you will know how to use Spark SQL, Machine Learning, Graph Computing and Structured Streaming Computingin Aziure Databricks.

Why Azure Databricks?

Productive :Launch your new Apache Spark environment in minutes.

Scalable :Globally scale your analytics and machine learning projects.

Trusted :Help protect your data and business with Azure AD integration, role-based controls and enterprise-grade SLAs.

Flexible :Build machine learning and AI solutions with your choice of language and deep learning frameworks.

This course contains both theory lectures ( slides are attached to download for reference) and a significant number of hands-on demos that helps you in gaining hands-on experience. This course help you in laying strong basic foundation in preparation of Microsoft Azure Cloud and Databricks.

In this course, you can not only learn azure databricks, but also learn and practice Machine Learning, Streaming Computing, Graph Analysis, installation and deployment of Open Source Apache spark.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: What is databricks?

Chapter 2: Databricks Quickstart

Lecture 1: Hands-on: How to navigate to the databricks service?

Lecture 2: Hands-on: How to create a workspace?

Lecture 3: Hands-on: How to create a spark cluster?

Lecture 4: Hands-on: How to create a notebook?

Lecture 5: Hands-on: How to create a table?

Lecture 6: Hands-on: How to delete a spark cluster?

Lecture 7: Hands-on: How to delete all resources in Azure Cloud?

Lecture 8: What is workspace?

Lecture 9: What is Resource Group?

Lecture 10: What is Databricks Runtime?

Lecture 11: What is Cluster?

Chapter 3: Apache Spark

Lecture 1: History of Hadoop

Lecture 2: What is Apache Spark?

Lecture 3: Hands-on: Download and install virtualbox

Lecture 4: Hands-on: Download and Install putty

Lecture 5: Hands-on: Download and Install winscp

Lecture 6: Hands-on: How to download HDP?

Lecture 7: Hands-on: How to set up HDP

Lecture 8: Hands-on: How to SSH into HDP with PuTTY?

Lecture 9: Hands-on: How to connect to HDP with WinSCP?

Lecture 10: Hands-on: How to connect to HDP with Web Shell?

Lecture 11: How to use ambari to manage Hadoop?

Lecture 12: Hands-on: Apache Spark Quick Start

Lecture 13: Apache Spark Architecture

Lecture 14: What is the ecosystem of Apache Spark?

Chapter 4: Databricks Developer Tools

Lecture 1: What is Databricks Developer tools?

Lecture 2: Hands-on: Download and install python

Lecture 3: Hands-on: How to set up databricks cli?

Lecture 4: Hands-on: How to use databricks cli?

Lecture 5: Hands-on: How to use Databricks Utilities?

Lecture 6: Hands-on: Download and install JDK

Lecture 7: Hands-on: Download and install IntelliJ IDEA

Lecture 8: Hands-on: Using Databricks Utilities API Library in IDE

Lecture 9: Hands-on: How to use databricks in Azure Data Factory

Lecture 10: Hands-on: How to debug the notebook in pipeline?

Lecture 11: Hands-on: ETL with Azure Databricks

Lecture 12: Hands-on: How to debug ETL notebook in ETL pipeline?

Chapter 5: Databricks Notebook

Lecture 1: What is notebook?

Lecture 2: Hands-on: Using notebook to visualize data

Chapter 6: Databricks Delta Lake

Lecture 1: Hands-on: Set up Apache Spark with Delta Lake

Lecture 2: Hands-on: Using python to operate delta lake

Chapter 7: Databricks REST API

Lecture 1: Hands-on: Download and install postman

Lecture 2: Hands-on: Generate a token

Lecture 3: Hands-on: Create a spark cluster using REST API

Lecture 4: Hands-on: Delete a spark cluster using REST API

Lecture 5: Hands-on: Permanently delete a spark cluster using REST API

Chapter 8: Databricks Machine Learning

Lecture 1: History of Artificial Intelligence

Lecture 2: What is Machine Learning?

Lecture 3: Workflow of Machine Learning

Lecture 4: Hands-on: Using scikit-learn with Spark on Databricks

Lecture 5: Hands-on: Using Spark to distribute parameter tuning

Lecture 6: Hands-on: Using tensorflow with Spark on Databricks

Lecture 7: Introduction to Distributed Deep Learning

Lecture 8: Distributed methods for using TensorFlow

Lecture 9: Hands-on: Distributed deep learning training using TensorFlow with HorovodRunner

Lecture 10: Hands-on: Using MLflow to track parameters and metrics

Lecture 11: History of Transfer Learning

Lecture 12: Hands-on: How to perform Transfer Learning on Databricks?

Chapter 9: Structured Streaming

Lecture 1: Hands-on: Create a virtual network

Lecture 2: Hands-on: Create an Kafka cluster on HDInsight

Lecture 3: Hands-on: How to connect to kafka using an SSH client

Lecture 4: Hands-on: Configure Kafka for IP advertising

Lecture 5: Hands-on: Peer the Kafka cluster to the Azure Databricks cluster

Lecture 6: Hands-on: Create an Apache Kafka topic

Lecture 7: Hands-on: Production Structured Streaming with Kafka

Lecture 8: Hands-on: Consumption Structured Streaming with Kafka

Chapter 10: Databricks Graph Analysis

Lecture 1: History of Graph Analytics

Lecture 2: Hands-on: How to install dataframes library?

Lecture 3: Hands-on: How to create a graph?

Chapter 11: Bonus: An Open Source Alternative Solution for Databricks

Lecture 1: Why use open source alternative solutions?

Lecture 2: How to deploy Cloudbreak on Azure Cloud?

Lecture 3: Using Cloudbreak to create a cluster

Instructors

Bigdata Engineer
Big Data, Artificial intelligence, Psychology

Rating Distribution

1 stars: 45 votes

2 stars: 20 votes

3 stars: 34 votes

4 stars: 19 votes

5 stars: 21 votes

Frequently Asked Questions

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