The Data Science and Big Data Analytics course gives down to earth establishment level preparing that empowers prompt and successful interest in Big Data and different Analytics ventures. It incorporates a prologue to Big Data and the Data Analytics lifecycle to address business challenges that influence Big Data. The course gives establishing in essential and progressed systematic techniques and a prologue to Big Data Analytics innovation and instruments. Lab sessions offer chances to see how these strategies and devices might be connected to true business challenges by a rehearsing Data Scientist. This course gives an industry accreditation to business investigators, information distribution center specialists or different experts with comparative foundations to help them change into the universe of Data Science and Big Data Analytics that has extraordinary difficulties and opportunities.
What is Big Data & Why Hadoop?
Big Data Characteristics, Challenges with traditional system
Hadoop Overview &it’s Ecosystem
Anatomy of Hadoop Cluster, Installing and Configuring Hadoop
HDFS – Hadoop Distributed File System
Name Nodes and Data Nodes
The HDFS command line and web interfaces
The HDFS Java API (lab)
Map Reduce Anatomy
How Map Reduce Works?
The Mapper & Reducer, Input Formats & Output Formats, Data Type & Customer Writable
Developing MapReduce Program
Setting up Eclipse Development Environment, Creating Map Reduce Projects,Debugging and Unit Testing MapReduce Code, Testing with MRUnit
More common algorithms: sorting, indexing and searching (lab)