Section 1 : Introduction, and Getting Started

 		Lecture 3 Note Alternate download link for the MovieLens data set Text
Lecture 4 Getting Started - Run your First MapReduce Program! 10:2

Section 2 : Understanding MapReduce

 		Lecture 5 MapReduce Basic Concepts
Lecture 6 A quick note on file names Text
Lecture 7 Walkthrough of Rating Histogram Code 10:39
Lecture 8 Understanding How MapReduce Scales Distributed Computing
Lecture 9 Average Friends by Age Example Part 1 3:5
Lecture 10 Average Friends by Age Example Part 2 7:14
Lecture 11 Minimum Temperature By Location Example 9:40
Lecture 12 Maximum Temperature By Location Example
Lecture 13 Word Frequency in a Book Example 5:26
Lecture 14 Making the Word Frequency Mapper Better with Regular Expressions 3:16
Lecture 15 Sorting the Word Frequency Results Using Multi-Stage MapReduce Jobs 8:18
Lecture 16 Activity Design a Mapper and Reducer for Total Spent by Customer 2:54
Lecture 17 Activity Write Code for Total Spent by Customer 3:57
Lecture 18 Compare Your Code to Mine 5:39
Lecture 19 Compare your Code to Mine for Sorted Results 3:49
Lecture 20 Combiners 7:27

Section 3 : Advanced MapReduce Examples

 		Lecture 21 Example Most Popular Movie 7:27
Lecture 22 Including Ancillary Lookup Data in the Example 8:1
Lecture 23 Example Most Popular Superhero, Part 1
Lecture 24 Example Most Popular Superhero, Part 2 6:31
Lecture 25 Example Degrees of Separation Concepts 12:28
Lecture 26 Degrees of Separation Preprocessing the Data 5:15
Lecture 27 Degrees of Separation Code Walkthrough 6:34
Lecture 28 Degrees of Separation Running and Analyzing the Results 5:41
Lecture 29 Example Similar Movies Based on Ratings Concepts 7:25
Lecture 30 Similar Movies Code Walkthrough 7:17
Lecture 31 Similar Movies Running and Analyzing the Results 6:37
Lecture 32 Learning Activity Improving our Movie Similarities MapReduce Job 3:58

Section 4 : Using Hadoop and Elastic MapReduce

 		Lecture 33 Fundamental Concepts of Hadoop 6:0
Lecture 34 The Hadoop Distributed File System (HDFS) 3:10
Lecture 35 Apache YARN 4:20
Lecture 36 Hadoop Streaming How Hadoop Runs your Python Code 3:37
Lecture 37 Setting Up Your Amazon Elastic MapReduce Account 6:49
Lecture 38 Linking Your EMR Account with MRJob 3:40
Lecture 39 Exercise Run Movie Recommendations on Elastic MapReduce 4:35
Lecture 40 Analyze the Results of Your EMR Job

Section 5 : Advanced Hadoop and EMR

 		Lecture 41 Distributed Computing Fundamentals 4:33
Lecture 42 Activity Running Movie Similarities on Four Machines 4:28
Lecture 43 Analyzing the Results of the 4-Machine Job 5:44
Lecture 44 Troubleshooting Hadoop Jobs with EMR and MRJob, Part 1 4:1
Lecture 45 Troubleshooting Hadoop Jobs, Part 2 10:28
Lecture 46 ml-1m Dataset Alternate Download Link Text
Lecture 47 Analyzing One Million Movie Ratings Across 16 Machines, Part 1 6:9
Lecture 48 Analyzing One Million Movie Ratings Across 16 Machines, Part 2 8:2

Section 6 : Other Hadoop Technologies

 		Lecture 49 Introducing Apache Hive 6:17
Lecture 50 Introducing Apache Pig 3:26
Lecture 51 Apache Spark Concepts 9:37
Lecture 52 Spark Example Part 1 11:15
Lecture 53 Spark Example Part 2 3:22
Lecture 54 Congratulations! 0:41