Learn Apache Spark with Python

Course Curriculum

Chapter 1: Module 1 Introduction to Spark with Python

Lecture 1: Introduction to the Module

Lecture 2: What is PySpark

Lecture 3: PySpark in Industry

Lecture 4: Why to go for Python

Chapter 2: Module 2 Introduction to Big Data and Hadoop

Lecture 1: Big Data Overview

Lecture 2: Facts about Big Data

Lecture 3: Big Data Scenarios

Lecture 4: Apache Hadoop Framework

Lecture 5: Top Hadoop Users

Lecture 6: HISTORY OF HADOOP

Lecture 7: Difference between RDBMS and Hadoop

Lecture 8: Cluster Modes in Hadoop

Lecture 9: Hadoop Ecosystem

Lecture 10: HDFS Daemons and Mapreduce daemons

Lecture 11: HADOOP CLUSTER ARCHITECTURE

Lecture 12: Top Reasons Why you should Learn Hadoop

Lecture 13: Hadoop distributions and compatibilities

Lecture 14: Hadoop Ecosystem in Detail

Lecture 15: Hadoop Distributed File System

Lecture 16: HDFS Files and Blocks

Lecture 17: HDFS components and architecture

Lecture 18: HDFS File Read and Write

Chapter 3: Module 3 Apache Spark Framework

Lecture 1: Batch and Real Time Analytics

Lecture 2: Why Spark when Hadoop is Already there

Lecture 3: Introduction to Apache Spark

Lecture 4: Features of Apache Spark

Lecture 5: Users and Use Cases of Apache Spark

Lecture 6: Job Execution Flow and Spark Execution

Lecture 7: Spark Unified Stack

Lecture 8: Complete Picture of Apache Spark

Lecture 9: Apache spark Architecture

Lecture 10: Top Companies Using Spark

Chapter 4: Module 4 Python Programming Language

Lecture 1: Getting Started with Python

Lecture 2: Introduction to Python

Lecture 3: Advantages and facts about python

Lecture 4: First python program

Lecture 5: Program execution and python IDE

Lecture 6: Built in types in python

Lecture 7: Numbers Data Type in Python

Lecture 8: String and List Data Type

Lecture 9: Dictionary, Tuples and Sets

Lecture 10: Variables and assignment

Lecture 11: Hands-On

Lecture 12: Hands-On

Lecture 13: Hands-On

Lecture 14: Hands-On

Lecture 15: Hands-On

Chapter 5: Module 5 Advanced Part of Apache Spark with Python

Lecture 1: Downloading and Installing Enthought Canopy

Lecture 2: Downloading and Installing jdk

Lecture 3: Downloading and Installing Spark

Lecture 4: Downloading and Setup of winutils

Lecture 5: Setting up Environment Variables

Lecture 6: Running the first Spark Program

Lecture 7: Downloading and Extracting movie ratings datasets

Lecture 8: Running Ratings Counter Spark Program

Lecture 9: Understanding key value pairs with an example

Lecture 10: Filtering RDD using an example

Lecture 11: Finding maximum temperature by location

Lecture 12: Map vs FlatMap

Lecture 13: Understanding FlatMap using Word Count example

Lecture 14: Sorting the word count results

Lecture 15: Total Amount Spent Example

Lecture 16: Sorting the Total Amount Spent Example result

Chapter 6: Module 6 Deep Dive Into Spark with Python

Lecture 1: Most popular movie example

Lecture 2: Understanding Broadcast Variables with an example

Lecture 3: Finding Similar Movies Example

Lecture 4: Finding Most Popular Superhero example

Lecture 5: Superhero Degrees of Separation Part1

Lecture 6: Superhero Degrees of Separation Part 2

Chapter 7: Module 7 SparkSQL in Apache Spark with Python

Lecture 1: Executing SQL commands

Lecture 2: Using SQL style functions instead of queries

Lecture 3: Using DataFrames instead of RDDs

Chapter 8: Module 8 MLib in Apache Spark with Python

Lecture 1: Using MLlib to produce movie recommendations

Lecture 2: Using Dataframe with MLlib using an example