PySpark – Build DataFrames with Python, Apache Spark and SQL

PySpark – Build DataFrames with Python, Apache Spark and SQL, available at $69.99, has an average rating of 4.4, with 35 lectures, based on 28 reviews, and has 206 subscribers.

You will learn about Create big data streaming pipelines with Spark using Python Learn how to apply Spark on distributed Dataframes Use Python with Big Data on a distributed framework (Apache Spark) This course is ideal for individuals who are Someone who knows Python and would like to learn how to use it for Big Data or Someone who is very familiar with another programming language and needs to learn Spark or Developers transferring from other languages or Python Developers looking to get better at Data Streaming or Spark Developers eager to expand their skills. It is particularly useful for Someone who knows Python and would like to learn how to use it for Big Data or Someone who is very familiar with another programming language and needs to learn Spark or Developers transferring from other languages or Python Developers looking to get better at Data Streaming or Spark Developers eager to expand their skills.

Enroll now: PySpark – Build DataFrames with Python, Apache Spark and SQL

Summary

Title: PySpark – Build DataFrames with Python, Apache Spark and SQL

Price: $69.99

Average Rating: 4.4

Number of Lectures: 35

Number of Published Lectures: 35

Number of Curriculum Items: 35

Number of Published Curriculum Objects: 35

Original Price: $199.99

Quality Status: approved

Status: Live

What You Will Learn

Create big data streaming pipelines with Spark using Python
Learn how to apply Spark on distributed Dataframes
Use Python with Big Data on a distributed framework (Apache Spark)

Who Should Attend

Someone who knows Python and would like to learn how to use it for Big Data
Someone who is very familiar with another programming language and needs to learn Spark
Developers transferring from other languages
Python Developers looking to get better at Data Streaming
Spark Developers eager to expand their skills.

Target Audiences

Someone who knows Python and would like to learn how to use it for Big Data
Someone who is very familiar with another programming language and needs to learn Spark
Developers transferring from other languages
Python Developers looking to get better at Data Streaming
Spark Developers eager to expand their skills.

This course covers all the fundamentals about Apache Spark streaming with Python and teaches you everything you need to know about developing Spark streaming applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Spark streaming and general big data manipulation skills to help your company to adapt Spark Streaming for building big data processing pipelines and data analytics applications. This course will be absolutely critical to anyone trying to make it in data science today.

Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrameframework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!

This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we’ve done that we’ll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way, you’ll have exercises and Mock Consulting Projects that put you right into a real-world situation where you need to use your new skills to solve a real problem!

We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30-day money-back guarantee and comes with a LinkedIn Certificate of Completion!

If you’re ready to jump into the world of Python, Spark, and Big Data, this is the course for you!

Course Curriculum

Chapter 1: 00 Course Overview

Lecture 1: Project Preview

Lecture 2: What Is Apache Spark

Lecture 3: What Are Resilient Distributed Datasets

Lecture 4: What Is A Dataframe

Lecture 5: What You'll Need

Lecture 6: Source Files

Chapter 2: 01 Mammoth Interactive Courses Introduction

Lecture 1: About Mammoth Interactive

Lecture 2: How To Learn Online Effectively

Lecture 3: Source Files

Chapter 3: 02 Introduction to Python (Prerequisite)

Lecture 1: Intro To Course And Python

Lecture 2: Variables

Lecture 3: Type Conversion Examples

Lecture 4: Operators

Lecture 5: Collections

Lecture 6: List Examples

Lecture 7: Tuples Examples

Lecture 8: Dictionaries Examples

Lecture 9: Ranges Examples

Lecture 10: Conditionals

Lecture 11: If Statement Examples

Lecture 12: Loops

Lecture 13: Functions

Lecture 14: Parameters And Return Values Examples

Lecture 15: Classes And Objects

Lecture 16: Inheritance Examples

Lecture 17: Static Members Examples

Lecture 18: Summary And Outro

Chapter 4: 03 Build DataFrames from Spreadsheets with PySpark

Lecture 1: Start A Spark Session

Lecture 2: Load Data As A CSV

Lecture 3: Perform Basic Dataframe Operations

Lecture 4: Format Dataframe Table

Lecture 5: Perform Dataframe Math Operations

Lecture 6: Perform Dataframe Queries

Lecture 7: Build SQL Queries With Spark

Lecture 8: Source Files

Instructors

Mammoth Interactive
Top-Rated Instructor, 3.3 Million+ Students
John Bura
Best Selling Instructor Web/App/Game Developer 1Mil Students

Rating Distribution

1 stars: 0 votes
2 stars: 1 votes
3 stars: 6 votes
4 stars: 7 votes
5 stars: 14 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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