Objective of this course is to impart knowledge on use of data mining techniques for deriving business intelligence to achieve organizational goals. Use of R (statistical computing software) to build, assess, and compare models based on real datasets and cases with an easy-to-follow learning curve.
INTENDED AUDIENCE: UG & PG engineering students: all branches, MBA students, Professionals working in or aspiring for Business Analyst, Data Analyst, Data Scientist, and Data Engineer rolesPREREQUISITES: Business Analytics & Data Mining Modeling Using RINDUSTRY SUPPORT:Big Data companies, Analytics & Consultancy companies, Companies with Analytics Division
COURSE LAYOUT Week 1 :Unsupervised Learning Methods : Association Rules
Week 2 : Unsupervised Learning Methods : Cluster Analysis
Week 3 :Time Series Forecasting: Understanding Time Series and Regression-Based Forecasting Methods
Week 4 :Time Series Forecasting: Smoothing Methods and Conclusion