Section 1 : Getting Started with Spark
Lecture 1 Introduction 00:01:39 Duration
Lecture 2 How to Use This Course 00:01:41 Duration
Lecture 3 INTRODUCTION TO BRAINMEASURES PROCTOR SYSTEM
Lecture 4 [Activity]Getting Set Up Installing Python, a J 00:14:42 Duration
Lecture 5 [Activity] Installing the MovieLens Movie Ratin 00:03:35 Duration
Lecture 6 [Activity] Run your first Spark program! Rating 00:06:12 Duration

Section 2 : Spark Basics and the RDD Interface
Lecture 1 What's new in Spark 3 00:06:49 Duration
Lecture 2 Introduction to Spark 00:10:11 Duration
Lecture 3 The Resilient Distributed Dataset (RDD) 00:12:35 Duration
Lecture 4 Ratings Histogram Walkthrough 00:13:28 Duration
Lecture 5 KeyValue RDD's, and the Average Friends by Age 00:16:08 Duration
Lecture 6 [Activity] Running the Average Friends by Age 00:05:40 Duration
Lecture 7 Filtering RDD's, and the Minimum Temperature b 00:08:12 Duration
Lecture 8 [Activity]Running the Minimum Temperature Exam 00:05:07 Duration
Lecture 9 [Activity] Running the Maximum Temperature by 00:03:19 Duration
Lecture 10 [Activity] Counting Word Occurrences using fla 00:07:25 Duration
Lecture 11 [Activity] Improving the Word Count Script wit 00:04:42 Duration
Lecture 12 [Activity] Sorting the Word Count Results 00:07:46 Duration
Lecture 13 [Exercise] Find the Total Amount Spent by Cust
Lecture 14 [Excercise] Check your Results, and Now Sort t 00:05:10 Duration
Lecture 15 Check Your Sorted Implementation and Results A 00:02:44 Duration

Section 3 : SparkSQL, DataFrames, and DataSets
Lecture 1 Introducing SparkSQL 00:09:29 Duration
Lecture 2 [Activity] Executing SQL commands and SQL-styl 00:07:52 Duration
Lecture 3 Using DataFrames instead of RDD's 00:07:40 Duration
Lecture 4 [Exercise] Friends by Age, with DataFrames 00:01:45 Duration
Lecture 5 Exercise Solution Friends by Age, with DataFra 00:07:55 Duration
Lecture 6 [Activity] Word Count, with DataFrames
Lecture 7 [Activity] Minimum Temperature, with DataFrame 00:10:27 Duration
Lecture 8 [Exercise] Implement Total Spent by Customer 00:02:08 Duration
Lecture 9 Exercise Solution Total Spent by Customer, wit 00:04:08 Duration

Section 4 : Advanced Examples of Spark Programs
Lecture 1 [Activity] Find the Most Popular Movie 00:04:16 Duration
Lecture 2 [Activity] Use Broadcast Variables to Display 00:10:34 Duration
Lecture 3 Find the Most Popular Superhero in a Social Gr
Lecture 4 [Activity] Run the Script - Discover Who the M 00:08:00 Duration
Lecture 5 [Exercise] Find the Most Obscure Superheroes 00:02:16 Duration
Lecture 6 Exercise Solution Most Obscure Superheroes 00:04:13 Duration
Lecture 7 Superhero Degrees of Separation Introducing Br
Lecture 8 Superhero Degrees of Separation Accumulators, 00:06:45 Duration
Lecture 9 [Activity] Superhero Degrees of Separation Rev 00:09:35 Duration
Lecture 10 Item-Based Collaborative Filtering in Spark 00:06:00 Duration
Lecture 11 [Activity] Running the Similar Movies Script u 00:13:43 Duration
Lecture 12 [Exercise] Improve the Quality of Similar Movi 00:03:05 Duration

Section 5 : Running Spark on a Cluster
Lecture 1 Introducing Elastic MapReduce 00:05:09 Duration
Lecture 2 [Activity] Setting up your AWS Elastic MapRed 00:09:58 Duration
Lecture 3 Partitioning 00:04:22 Duration
Lecture 4 Create Similar Movies from One Million Ratings 00:11:27 Duration
Lecture 5 [Activity] Create Similar Movies from One Mill 00:11:27 Duration
Lecture 6 Create Similar Movies from One Million Ratings 00:03:30 Duration
Lecture 7 Troubleshooting Spark on a Cluster 00:03:44 Duration
Lecture 8 More Troubleshooting, and Managing Dependencie 00:06:02 Duration

Section 6 : Machine Learning with Spark ML
Lecture 1 Introducing MLLib 00:06:04 Duration
Lecture 2 [Activity] Using Spark ML to Produce Movie Rec 00:09:55 Duration
Lecture 3 Analyzing the ALS Recommendations Results
Lecture 4 [Activity] Linear Regression with Spark ML 00:13:26 Duration
Lecture 5 [Exercise] Using Decision Trees in Spark ML to 00:05:34 Duration
Lecture 6 Exercise Solution Decision Trees with Spark 00:06:20 Duration

Section 7 : Spark Streaming, Structured Streaming, and GraphX
Lecture 1 Spark Streaming 00:08:04 Duration
Lecture 2 [Activity] Structured Streaming in Python 00:08:48 Duration
Lecture 3 [Exercise] Use Windows with Structured Streami 00:05:50 Duration
Lecture 4 Exercise Solution Using Structured Streaming w 00:06:38 Duration
Lecture 5 GraphX 00:02:11 Duration