BIG DATA ANALYTICS FOR BUSINESS (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: define Define big data analytics concepts and the use for business; describe Describe the collection of data and techniques for pre-processing the data before applying analytics; apply Apply big data analytics and visualization; analyze Analyse trends related to big data analytics and big data case studies.

Topics :

Introduction to Big Data Analytics; Getting to Know Your Data: Data Pre-processing; Getting to Know Your Data: Data Pre-processing; Getting to Know Your Data: Data Pre-processing; Decision Tree Classification; Decision Tree Classification; Decision Tree Classification; Decision Tree Classification; Bayes Classification; Bayes Classification; Bayes Classification; Bayes Classification; Classification: Advanced Methods – Lazy Learners (or Learning from Your Neighbors); Classification: Advanced Methods – Lazy Learners (or Learning from Your Neighbors); Analyzing Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods; Analyzing Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods; Advanced Pattern Analysis;Advanced Pattern Analysis; Cluster Analysis: Basic Concepts and Methods; Cluster Analysis: Basic Concepts and Methods; Cluster Analysis: Basic Concepts and Methods; Cluster Analysis: Basic Concepts and Methods; Big Data Analytics Trends; Big Data Analytics Trends; Big Data Case Studies & Project presentation; Big Data Case Studies & Project presentation.