We are looking forward to sharing many exciting stories and examples of analytics with all of you using python programming language. This course includes examples of analytics in a wide variety of industries, and we hope that students will learn how you can use analytics in their career and life. One of the most important aspects of this course is that you, the student, are getting hands-on experience creating analytics models; we, the course team, urge you to participate in the discussion forums and to use all the tools available to you while you are in the course!INTENDED AUDIENCE : Management, Industrial Engineering and Computer Science Engineering StudentsPREREQUISITES : NillINDUSTRY SUPPORT : Any analytics company
Overview
Syllabus
Week 1 : Introduction to data analytics and Python fundamentalsWeek 2 : Introduction to probabilityWeek 3 : Sampling and sampling distributionsWeek 4 : Hypothesis testingWeek 5 : Two sample testing and introduction to ANOVAWeek 6 : Two way ANOVA and linear regressionWeek 7 : Linear regression and multiple regressionWeek 8 : Concepts of MLE and Logistic regressionWeek 9 : ROC and Regression Analysis Model BuildingWeek 10 : c2Test and introduction to cluster analysisWeek 11 : Clustering analysisWeek 12 : Classification and Regression Trees (CART)
Taught by
Prof. A Ramesh
