Apache Spark with Python Learn by Doing
- Development
- May 03, 2025

Apache Spark with Python – Learn by Doing, available at $39.99, has an average rating of 3.55, with 33 lectures, 4 quizzes, based on 150 reviews, and has 1012 subscribers.
You will learn about 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 This course is ideal for individuals who are People looking for career growth and new opportunities or People curious if Spark with Python could be good solution for their technical challenges or People who do not want to evolve or learn new ways to do things should NOT take this course It is particularly useful for People looking for career growth and new opportunities or People curious if Spark with Python could be good solution for their technical challenges or People who do not want to evolve or learn new ways to do things should NOT take this course.
Enroll now: Apache Spark with Python – Learn by Doing
Summary
Title: Apache Spark with Python – Learn by Doing
Price: $39.99
Average Rating: 3.55
Number of Lectures: 33
Number of Quizzes: 4
Number of Published Lectures: 31
Number of Published Quizzes: 4
Number of Curriculum Items: 37
Number of Published Curriculum Objects: 35
Original Price: $29.99
Quality Status: approved
Status: Live
What You Will Learn
Who Should Attend
Target Audiences
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:
Course Curriculum
Chapter 1: Course Overview
Lecture 1: Course Overview and Methodology
Chapter 2: Apache Spark and Python Foundational Building Blocks
Lecture 1: The Big Picture – Running Some Code, Analyzing Data with Apache Spark
Lecture 2: Apache Spark Fundamentals – The Essentials You Need to Know
Chapter 3: Prepare Your Environment
Lecture 1: Setting Up Your Environment
Lecture 2: For Windows Operating System Users Only
Lecture 3: Download and Install Spark
Lecture 4: Download and Install Python
Lecture 5: [Milestone] Setup Checkpoint
Lecture 6: Check ipython notebook Setup (optional)
Lecture 7: Sample Data Access
Lecture 8: [Milestone] Setup References and Download Links
Chapter 4: Apache Spark Transformations and Actions
Lecture 1: Spark Transformations and Actions Overview
Lecture 2: Spark Transformations Part 1
Lecture 3: Spark Transformations Part 2
Lecture 4: Spark Transformations Part 3
Lecture 5: Spark Actions
Lecture 6: [Milestone] Download Resources and Source Code Access
Chapter 5: Apache Spark Clusters
Lecture 1: Spark on a Cluster Introduction
Lecture 2: Run Standalone Cluster
Lecture 3: Deploy Python Programs to the Cluster
Lecture 4: [Milestone] Write and Deploy Python Program to the Spark Cluster
Lecture 5: Spark Cluster Administrative Diagnostics – The Spark UI
Lecture 6: Create an Amazon EC2 Based Cluster Part 1
Lecture 7: [Milestone] Create an Amazon EC2 Based Cluster Part 2
Chapter 6: Spark SQL
Lecture 1: Spark SQL Introduction
Lecture 2: Spark SQL with New York City Uber Trips CSV Source
Lecture 3: Spark SQL with Historical World Cup Player Statistics JSON Source
Lecture 4: Spark SQL with mySQL (JDBC) source
Lecture 5: [Milestone] Spark SQL Resources and Download Source Code
Chapter 7: Conclusion and Free Bonus Lecture
Lecture 1: Apache Spark with Python Course Conclusion and Looking Ahead
Lecture 2: Bonus Lecture: Access to Free Books and Course Discounts
Instructors

Todd McGrath
Data Engineer, Software Developer, Mentor
Rating Distribution
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!
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