PG Certificate Program in Artificial Intelligence and Deep Learning

Advance Text Analytics
Natural Language Processing
Recurrent Neural Networks- RNN
Time Series Analysis with RNN
Variations of RNN- LSTM and GRU Building and Training an RNN for Speech Recognition Developing Chatbots

What is ML, Need for ML, classification of ML algorithms- supervised and unsupervised learning.
Types of ML algorithms

Classification and Regression – understanding classification and regression techniques with case studies

Introduction to Scikit- learn package in python.
Implementing ML algorithms in python using Scikit-learn

Linear, Logistic regression; Decision trees
Support Vector Machines. Python hand on using Scikit-learn

Creating training models using ML algorithms and deploying the models,
Understand how to deploy models after training

Basics of text processing, lexical processing, syntax and semantics of text processing,
other problems in text analytics

Introduction and applications of NLP.
Learning the business use cases of Natural language processing. Statistical NLP and text similarity,
syntax and parsing techniques, text summarization techniques, semantics and generation

What is a Perceptron?
Perceptron Training
Implementing a perceptron
Recap of Matrix Multiplication
Deep Neural Networks
Training Neural networks with Tensorflow
Types of NN- CNN, RNN, Feedforward, GAN.
Common Tensorflow API - KERAS,
Introduction to Reinforcement Learning