Hands-on Machine Learning Driven Business Analytics- Zero Code Approach with Case-Studies

Objective

Apart from basics of machine learning concepts, Participants would be introduced to real life scenarios through case-study method, where Statistical and Machine Learning concepts will be applied to solve business/data problems. This course takes a deep dive to explain and interpret the machine learning output in the context of business problem.

There would be a bridge course (which will be offered before the main course starts for about 3 to 6 hours) on Mathematics and Statistics, that can be taken up by the students who would like to refresh their statistical concepts. Content of Bridge course : Central Tendency (Mean, Median, Mode) , Random Variables – Discrete, Continuous, Probability Density Function, Normal distribution, Central Limit Theorem, Standard Normal Distribution , Probability Computation, Estimation, Confidence Interval

Note: It’s recommended that all students should take it to enable faster learning during main course.

Syllabus

Introduction of statistical inferences, Exploratory data analysis, Data preprocessing, hypothesis, machine learning, different types of machine learning (supervised:, Regression, classification, , time-series, decision tree, random forest, unsupervised learning : clustering, factor analysis, PCA),  Overview deep learning.