A Crash Course In PySpark
A Crash Course In PySpark, available at $49.99, has an average rating of 4.5, with 20 lectures, based on 4717 reviews, and has 25113 subscribers.
You will learn about PySpark, Apache Spark, Big Data Analytics, Big Data Processing, Python This course is ideal for individuals who are People wanting to leverage their big data with Spark It is particularly useful for People wanting to leverage their big data with Spark.
Enroll now: A Crash Course In PySpark
Summary
Title: A Crash Course In PySpark
Price: $49.99
Average Rating: 4.5
Number of Lectures: 20
Number of Published Lectures: 20
Number of Curriculum Items: 20
Number of Published Curriculum Objects: 20
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- PySpark, Apache Spark, Big Data Analytics, Big Data Processing, Python
Who Should Attend
- People wanting to leverage their big data with Spark
Target Audiences
- People wanting to leverage their big data with Spark
Spark is one of the most in-demand Big Data processing frameworks right now.
This course will take you through the core concepts of PySpark. We will work to enable you to do most of the things you’d do in SQL or Python Pandas library, that is:
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Getting hold of data
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Handling missing data and cleaning data up
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Aggregating your data
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Filtering it
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Pivoting it
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And Writing it back
All of these things will enable you to leverage Spark on large datasets and start getting value from your data.
Let’s get started.
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction
Lecture 2: How is this course structured
Chapter 2: A Scenario To Get Us Started
Lecture 1: Introduction to our development environment
Lecture 2: Introduction to our dataset & dataframes
Lecture 3: Latest Config Code
Lecture 4: Environment configuration code (latest code in downloadable file)
Lecture 5: Ingesting & Cleaning Data
Lecture 6: Answering our scenario questions
Chapter 3: Core Concepts
Lecture 1: Bringing data into dataframes
Lecture 2: Inspecting A Dataframe
Lecture 3: Handling Null & Duplicate Values
Lecture 4: Selecting & Filtering Data
Lecture 5: Applying Multiple Filters
Lecture 6: Running SQL on Dataframes
Lecture 7: Adding Calculated Columns
Lecture 8: Group By And Aggregation
Lecture 9: Writing Dataframe To Files
Chapter 4: Challenge
Lecture 1: Challenge Overview
Lecture 2: Challenge Solution
Chapter 5: Conclusion
Lecture 1: Thanks for joining me to learn PySpark!
Instructors
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Kieran Keene
Data Engineer at Kodey
Rating Distribution
- 1 stars: 22 votes
- 2 stars: 41 votes
- 3 stars: 424 votes
- 4 stars: 1906 votes
- 5 stars: 2338 votes
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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