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 You'll learn about the basic use of Azure Cloud You will learn to deploy Apache Spark ecosystems locally You'll 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 You'll learn how to use Azure Data Factory You'll learn the historical story of Apache Hadoop, Apache Spark and Graph Analysis You'll 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
- You'll learn about the basic use of Azure Cloud
- You will learn to deploy Apache Spark ecosystems locally
- You'll 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
- You'll learn how to use Azure Data Factory
- You'll learn the historical story of Apache Hadoop, Apache Spark and Graph Analysis
- You'll 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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