Apache Spark with Databricks
Apache Spark with Databricks, available at $49.99, has an average rating of 3.75, with 34 lectures, 5 quizzes, based on 298 reviews, and has 1178 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 learn to Provision your own Databricks workspace using Azure cloud. You will be able to create application on Azure Databricks after completing the course You will be able to process continual streams of data with Spark streaming using azure event Hub Transform structured data using SparkSQL and Dataframes Build a binary classification application using the Mlib pipelines API. This course is ideal for individuals who are Anyone who wants to learn Spark using Azure Databricks It is particularly useful for Anyone who wants to learn Spark using Azure Databricks.
Enroll now: Apache Spark with Databricks
Summary
Title: Apache Spark with Databricks
Price: $49.99
Average Rating: 3.75
Number of Lectures: 34
Number of Quizzes: 5
Number of Published Lectures: 34
Number of Published Quizzes: 5
Number of Curriculum Items: 39
Number of Published Curriculum Objects: 39
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 learn to Provision your own Databricks workspace using Azure cloud.
- You will be able to create application on Azure Databricks after completing the course
- You will be able to process continual streams of data with Spark streaming using azure event Hub
- Transform structured data using SparkSQL and Dataframes
- Build a binary classification application using the Mlib pipelines API.
Who Should Attend
- Anyone who wants to learn Spark using Azure Databricks
Target Audiences
- Anyone who wants to learn Spark using Azure Databricks
In this course you will learn the basics of creating Spark jobs, loading data, and working with data. You’ll also get an introduction to running machine learning algorithms and working with streaming data. Databrickslets you start writing Spark queries instantly so you can focus on your data problems.
Azure Databricks accelerate big data analytics and artificial intelligence (AI) solutions, a fast, easy and collaborative Apache Spark–based analytics service.
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.
We believe that when you learn something, you should be able to apply it somewhere. So, in this course, we are also providing you with some of the important spark interview questions , which will help you to crack the interview with flying colors.
We believe that when you learn something, you should be able to apply it somewhere. So, in this course, we are also providing you with some of the important spark interview questions , which will help you to crack the interview with flying colors.
Course Curriculum
Chapter 1: Overview
Lecture 1: Course Overview
Lecture 2: Big Data trunk Introduction !!
Chapter 2: Apache Spark Introduction
Lecture 1: Big Data before Spark
Lecture 2: Big Data After Spark
Lecture 3: Introduction to Apache Spark
Lecture 4: Spark – RDD
Lecture 5: Lab – Ways for creating RDD
Lecture 6: Spark Application Architecture
Lecture 7: Spark Operations – Transformation & Action
Lecture 8: Lab – Transformation & Action
Lecture 9: DAG (Direct Acyclic Graph)
Chapter 3: Databricks with Microsoft Azure
Lecture 1: Spark Databricks Analytics in Azure
Lecture 2: Why Databricks ?
Lecture 3: Provisioning Databricks workspace in Azure portal
Lecture 4: Using Databricks community Edition
Chapter 4: Understanding Cluster and Notebooks in Databricks
Lecture 1: Use notebook in Databricks
Chapter 5: Working with Spark in Databricks
Lecture 1: Spark SQL
Lecture 2: Developing Spark application
Lecture 3: Removing Stopwords
Lecture 4: Developing Spark ML application
Lecture 5: Developing Spark Streaming applications (real time Twitter Data)
Lecture 6: Optimizing Spark Performance
Chapter 6: Spark Interview
Lecture 1: Spark Vs Hadoop / mapReduce
Lecture 2: Spark Core
Lecture 3: Something more about RDD
Lecture 4: Type Safety in Dataset
Lecture 5: Justify Lazy Evaluation in Spark
Lecture 6: Explain Fault Tolerance in Spark
Lecture 7: Coalesce and Repartition
Lecture 8: Spark Executor Memory
Lecture 9: Garbage Collection Optimization in Spark
Lecture 10: Learn More on Spark Interview
Chapter 7: Bonus Section
Lecture 1: Thanks You looking way forward !!
Lecture 2: Bonus Lecture
Instructors
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Big Data Trunk
All about Big Data and Hadoop
Rating Distribution
- 1 stars: 43 votes
- 2 stars: 41 votes
- 3 stars: 83 votes
- 4 stars: 74 votes
- 5 stars: 57 votes
Frequently Asked Questions
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