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:

Getting hold of data
Handling missing data and cleaning data up
Aggregating your data
Filtering it
Pivoting it
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

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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