MODULES

OUTCOMES

BASIC STATISTICS AND ITS APPLICATION :

Introduction to Statistical tools and hypothesis testing

In this module, students will understand the basic concept of statistics like probability distribution functions and hypothesis testing.

DATA HANDLING AND DATA PREPARATION :

Basic of different type of data used in machine learning.

In this module, students will understand the concept data in machine learning, how to clean and repair dataset, training and test set etc.

MACHINE LEARNING :

Working with regression and classication models

In this modele, students will understand the concept of machine learning like linear regression model, classification models like Naive Bayes, SVM, KNN, Logistic, Random Forest etc.

RECOMMENDATION SYSTEM :

Working with different recommendation system.

In this module, students will understand the concept of recommendation system like item-item similarity user-user similarity, popularity based model etc.

ARTIFICIAL INTELLEGENCE AND DEEP NEURAL NETWORK :

Working with deep neural network

In this module, students will understand the concept of standard neural network and convolutional neural network, RNN and LSTM.