Lecture 1 - Introduction to Big Data
Lecture 2 - Big Data Enabling Technologies
Lecture 3 - Hadoop Stack for Big Data
Lecture 4 - Hadoop Distributed File System (HDFS)
Lecture 5 - Hadoop MapReduce 1.0
Lecture 6 - Hadoop MapReduce 2.0 - Part I
Lecture 7 - Hadoop MapReduce 2.0 - Part II
Lecture 8 - MapReduce Examples
Lecture 9 - Parallel Programming with Spark
Lecture 10 - Introduction to Spark
Lecture 11 - Spark Built-in Libraries
Lecture 12 - Design of Key-Value Stores
Lecture 13 - Data Placement Strategies
Lecture 14 - CAP Theorem
Lecture 15 - Consistency Solutions
Lecture 16 - CQL (Cassandra Query Language)
Lecture 17 - Design of Zookeeper
Lecture 18 - Design of HBase
Lecture 19 - Spark Streaming and Sliding Window Analytics - Part I
Lecture 20 - Spark Streaming and Sliding Window Analytics - Part II
Lecture 21 - Sliding Window Analytics
Lecture 22 - Introduction to Kafka
Lecture 23 - Big Data Machine Learning - Part I
Lecture 24 - Big Data Machine Learning - Part II
Lecture 25 - Machine Learning Algorithm K-means using Map Reduce for Big Data Analytics
Lecture 26 - Parallel K-means using Map Reduce on Big Data Cluster Analysis
Lecture 27 - Decision Trees for Big Data Analytics
Lecture 28 - Big Data Predictive Analytics - Part I
Lecture 29 - Big Data Predictive Analytics - Part II
Lecture 30 - Parameter Servers
Lecture 31 - PageRank Algorithm in Big Data
Lecture 32 - Spark GraphX and Graph Analytics - Part I
Lecture 33 - Spark GraphX and Graph Analytics - Part II
Lecture 34 - Case Study: Flight Data Analysis using Spark GraphX
