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Development Programming Languages Apache Spark

Apache Spark with Python - Learn by Doing

50 Python source code examples and multiple deployment scenarios
Rating: 3.7 out of 53.7 (150 ratings)
1,008 students
Created by Todd McGrath
Last updated 2/2016
English
English [Auto]
30-Day Money-Back Guarantee

What you'll learn

  • Have confidence using Spark from Python
  • Understand Spark core concepts and processing options
  • Run Spark and Python on their own computer
  • Setup Spark on new Amazon EC2 cluster
  • Deploy Python Programs to to a Spark Cluster
  • Know what tools to use for Spark Adminstration
  • Certificate of completion
  • 30 money back guarantee

Course content

7 sections • 31 lectures • 1h 56m total length

  • Preview03:52

  • The Big Picture - Running Some Code, Analyzing Data with Apache Spark
    Preview08:57
  • Apache Spark Fundamentals - The Essentials You Need to Know
    05:59
  • [Milestone] Key Concepts Quiz
    3 questions

  • Setting Up Your Environment
    00:38
  • For Windows Operating System Users Only
    02:32
  • Download and Install Spark
    04:07
  • Download and Install Python
    02:26
  • [Milestone] Setup Checkpoint
    01:34
  • Check ipython notebook Setup (optional)
    02:14
  • Sample Data Access
    01:46
  • [Milestone] Setup References and Download Links
    1 page

  • Spark Transformations and Actions Overview
    02:34
  • Spark Transformations Part 1
    13:16
  • Spark Transformations Part 2
    05:18
  • Spark Transformations Part 3
    06:31
  • [Milestone] Transformations Quiz
    3 questions
  • Spark Actions
    09:12
  • [Milestone] Spark Actions Quiz
    2 questions
  • [Milestone] Download Resources and Source Code Access
    00:05

  • Spark on a Cluster Introduction
    04:17
  • Run Standalone Cluster
    01:38
  • Deploy Python Programs to the Cluster
    01:43
  • [Milestone] Write and Deploy Python Program to the Spark Cluster
    03:48
  • Spark Cluster Administrative Diagnostics - The Spark UI
    02:02
  • Create an Amazon EC2 Based Cluster Part 1
    05:54
  • [Milestone] Create an Amazon EC2 Based Cluster Part 2
    02:54
  • [Milestone] Spark Cluster Quiz
    3 questions

  • Preview03:13
  • Spark SQL with New York City Uber Trips CSV Source
    06:33
  • Spark SQL with Historical World Cup Player Statistics JSON Source
    06:19
  • Spark SQL with mySQL (JDBC) source
    04:38
  • [Milestone] Spark SQL Resources and Download Source Code
    00:03

  • Apache Spark with Python Course Conclusion and Looking Ahead
    00:58
  • Bonus Lecture: Access to Free Books and Course Discounts
    00:11

Requirements

  • Need a computer to run examples
  • Familiar with Python. Expertise not required, just basic understanding.

Description

Would you like to advance your career and learning Apache Spark will help?

There's no doubt Apache Spark is an in-demand skillset with higher pay. This course will help you get there.

This course prepares you for job interviews and technical conversations. At the end of this course, you can update your resume or CV with a variety of Apache Spark experiences.

Or maybe you need to learn Apache Spark quickly for a current or upcoming project?

How can this course help?

You will become confident and productive with Apache Spark after taking this course. You need to be confident and productive in Apache Spark to be more valuable.

Now, I'm not going to pretend here. You are going to need to put in work. This course puts you in a position to focus on the work you will need to complete.

This course uses Python, which is a fun, dynamic programming language perfect for both beginners and industry veterans.

At the end of this course, you will have rock solid foundation to accelerate your career and growth in the exciting world of Apache Spark.

Why choose this course?

Let's be honest. You can find Apache Spark learning material online for free. Using these free resources is okay for people with extra time.

This course saves your time and effort. It is organized in a step-by-step approach that builds upon each previous lessons. PowerPoint presentations are minimal.

The intended audience of this course is people who need to learn Spark in a focused, organized fashion. If you want a more academic approach to learning Spark with over 4-5 hours of lectures covering the same material as found here, there are other courses on Udemy which may be better for you.

This Apache Spark with Python course emphasizes running source code examples.

All source code examples are available for download, so you can execute, experiment and customize for your environment after or during the course.

This Apache Spark with Python course covers over 50 hands-on examples. We run them locally first and then deploy them on cloud computing services such as Amazon EC2.

The following will be covered and more:

  • What makes Spark a power tool of Big Data and Data Science?
  • Learn the fundamentals of Spark including Resilient Distributed Datasets, Spark Actions and Transformations
  • Run Spark in a Cluster in your local environment and Amazon EC2
  • Deploy Python applications to a Spark Cluster
  • Explore Spark SQL with CSV, JSON and mySQL (JDBC) data sources
  • Convenient links to download all source code
  • Reinforce your understanding through multiple quizzes and lecture recap


Who this course is for:

  • People looking for career growth and new opportunities
  • People curious if Spark with Python could be good solution for their technical challenges
  • People who do not want to evolve or learn new ways to do things should NOT take this course

Instructor

Todd McGrath
Data Engineer, Software Developer, Mentor
Todd McGrath
  • 3.7 Instructor Rating
  • 307 Reviews
  • 2,272 Students
  • 3 Courses

Todd has an extensive and proven track record in software development leadership and building solutions for the world's largest brands and Silicon Valley startups.

His courses are taught using the same skills used in his consulting and mentoring projects.  Todd believes the only way to gain confidence and become productive is to be hands-on through examples.  Each new subject should build upon previous examples or presentation, so each step is also a way to reemphasis a prior topic.

To learn more about Todd, visit his LinkedIn profile. 

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