PySpark Crash Course – Learn Analytics with Spark, Quickly!

PySpark Crash Course – Learn Analytics with Spark, Quickly!, available at $19.99, has an average rating of 4.7, with 36 lectures, based on 15 reviews, and has 91 subscribers.

You will learn about Learn to load data into PySpark dataframes Learn to wrangle your data to clean, handle nulls & handle duplicates Learn to create calculated fields, aggregate your data & extract insights Learn to implement advanced PySpark techniques such as window functions and user-defined functions (UDFs) This course is ideal for individuals who are Anyone with a desire to learn Apache Spark – to enhance their careers or break into the field of data engineering It is particularly useful for Anyone with a desire to learn Apache Spark – to enhance their careers or break into the field of data engineering.

Enroll now: PySpark Crash Course – Learn Analytics with Spark, Quickly!

Summary

Title: PySpark Crash Course – Learn Analytics with Spark, Quickly!

Price: $19.99

Average Rating: 4.7

Number of Lectures: 36

Number of Published Lectures: 36

Number of Curriculum Items: 36

Number of Published Curriculum Objects: 36

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Learn to load data into PySpark dataframes
Learn to wrangle your data to clean, handle nulls & handle duplicates
Learn to create calculated fields, aggregate your data & extract insights
Learn to implement advanced PySpark techniques such as window functions and user-defined functions (UDFs)

Who Should Attend

Anyone with a desire to learn Apache Spark – to enhance their careers or break into the field of data engineering

Target Audiences

Anyone with a desire to learn Apache Spark – to enhance their careers or break into the field of data engineering

Ready to dive into the fascinating world of Apache Spark (PySpark)? This course is your ticket to unraveling the mysteries of Spark, starting from the ground up and zooming all the way into some seriously cool stuff like window functions and user-defined functions (UDFs).

What You’ll Discover:

Playing with Data: Get your hands dirty with Spark SQL and learn how to wield DataFrames like a pro, mastering the art of manipulating, filtering, and crunching data.
Next-Level Tricks: Ever heard of window functions or UDFs? We’ll guide you through these advanced concepts, empowering you to perform super-smart analytics and craft custom functions for your data.

Why This Course Rocks: We’re all about making it count! Instead of dragging things out, we’re here to give you the essential skills pronto. We believe that having the core knowledge means you can jump right into action.

Who’s Welcome Here:

Data wizards (and those aspiring to be one)
Tech enthusiasts hungry for big data action
Anyone itching to explore Spark and take their data skills up a notch

How We Roll:

Short and Sweet: Bite-sized modules for quick learning bursts.
Hands-On Fun: Dive into real-world examples and projects for that practical edge.

What’s in Store for You: Once you’ve completed this ride, you’ll be armed with a solid Spark foundation. You’ll confidently handle data, wield window functions like a champ, and even create your own custom UDFs. Get ready to tackle real-world data puzzles and unearth meaningful insights from big datasets.
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Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Intro

Lecture 2: Exploring The Data

Lecture 3: Our Development Environment

Chapter 2: Basics

Lecture 1: Ingesting Our Data

Lecture 2: Inspecting Our Dataframe

Lecture 3: Creating a custom schema

Lecture 4: Handling Null Values

Lecture 5: Running SQL on our dataframes

Lecture 6: Group by & Aggregation

Lecture 7: Creating Calculated Fields

Lecture 8: Handling Duplicates

Lecture 9: Writing to Files

Chapter 3: Case Statements (When)

Lecture 1: Case Statements: Section 1

Lecture 2: Case Statements: Section 2

Lecture 3: Case Statements: Section 3

Lecture 4: Case Statements: Section 4

Lecture 5: Case Statement: Challenge

Lecture 6: Case Statement: Solution

Chapter 4: Window Functions

Lecture 1: Rank Window Function

Lecture 2: Row Number Window Function

Lecture 3: Lead / Lag Window Function

Lecture 4: Sum Window Function

Lecture 5: Window Function Challenge

Lecture 6: Window Function Challenge Solution

Chapter 5: Filtering Dataframes

Lecture 1: Filtering Dataframes: 1

Lecture 2: Filtering Dataframes: 2

Lecture 3: Filtering Dataframes: 3

Lecture 4: Filtering Dataframes: 4

Chapter 6: UDFs (User Defined Functions)

Lecture 1: UDFs: 1

Lecture 2: UDFs: 2

Lecture 3: UDF: Challenge

Lecture 4: UDF: Challenge Solution

Chapter 7: Working With Datetimes

Lecture 1: Working with Datetimes

Lecture 2: Datetime: Challenge

Lecture 3: Datetime: Solution

Chapter 8: Wrapping Up

Lecture 1: Congratulations!

Instructors

Kieran Keene
Data Engineer at Kodey

Rating Distribution

1 stars: 0 votes
2 stars: 0 votes
3 stars: 0 votes
4 stars: 4 votes
5 stars: 11 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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