NOC:Big Data Computing


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