Post Graduate Program in Artificial Intelligence and Machine Learning 

offered by Work Integrated Learning Programmes

Course 1

Overview of certificate programme in ML & AI

Introduction to Regression

Mathematics Foundations

Model Building using Least squares

Model Accuracy & Selection

Overfitting

Interpretability of regression models

Course 2

Overview of Feature Engineering

Data Preprocessing

Dimensionality Reduction

Visualization

Course 3

Overview of the Classification Module

Nearest-neighbour Methods

Naïve Bayes Classifier

Logistic Regression

Decision Tree

Optimization Foundations for Support Vector Machines

Support Vector Machines

Support Vector Machines in overlapping class distributions & Kernels

Ensemble Methods

Course 4

Introduction to Unsupervised Learning, Clustering

K-Means Algorithm, K-Means – Variations, Detecting Outliers

Math Fundamentals for EM Algorithm, EM Algorithm, Clustering for Customer Segmentation

Hierarchical Clustering

Density Based Clustering, Clustering for Anomaly Detection

Assessing Quality of Clustering, Significance of Clustering - Interpreting/ summarizing Clusters by businesses

Association Rule Mining, Apriori Algorithm

Time series Prediction and Markov Process, Hidden Markov Model

Course 5

Document vectorization and Parts of Speech Tagging

Introduction to Part of speech tagging, Part of speech tagging using HMM-1, Implementing POS Tagging in Python

Topic modelling using LDA

Introduction to Sentiment Analysis

Recommender Systems

Course 6

Artificial Neural Network

Sequence Modeling in Neural Network

Deep Learning

Convolution Networks with Deep Learning

Autoencoders with Deep Learning

Generative deep learning models

CAPSTONE PROJECT