PG Certificate Program in Artificial Intelligence & Deep Learning

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Overview
  • Access to Community
    Peer to peer learning through online/live meetups and webinars/techtalks on emerging technologies and their evolution.
  • Hands on tool
    Apply Tensorflow, Scikit Learn library, Keras and other machine learning and deep learning tools.
  • Who Should Attend
    IT professionals and consultants, Graduates with an IT background
  • Salary Packages
    The average pay for an AI professional with 2-4 years of experience is ₹15-20 lakhs per year
  • Online Live Sessions
    Learn from experts with a vast experience in delivering artificial intelligence course.
Access to Community
Peer to peer learning through online/live meetups and webinars/techtalks on emerging technologies and their evolution.
Hands on tool
Apply Tensorflow, Scikit Learn library, Keras and other machine learning and deep learning tools.
Who Should Attend
IT professionals and consultants, Graduates with an IT background
Salary Packages
The average pay for an AI professional with 2-4 years of experience is ₹15-20 lakhs per year
Online Live Sessions
Learn from experts with a vast experience in delivering artificial intelligence course.
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Course Curriculum
1.1 Introduction to AI

Sneak Peek into the future
Applications of AI
Enterprise use - Automotive, Manufacturing, Healthcare, Retail
Consumer use -Games, Home Automation
Introduction to Machine learning and Deep Learning

1.2 Machine Learning

Types of Machine learning
Popular ML algorithms - Linear Regression, SVM, Decision Trees etc.
Training and Deploying models.
ML With SKLearn using Python

1.3 Programming with TensorFlow

Introduction to Tensorflow
Programming structure in Tensorflow
Regression and classification with Tensorflow

2.1 Introduction to Neural Networks

Perceptron and Deep Neural Networks
Training Neural networks with Tensorflow
Types of NN- CNN, RNN, Feedforward, GAN.
Common Tensorflow API's - KERAS, Estimator, Layers
Introduction to Reinforcement Learning

2.2 Image recognition

Introduction to Image processing and Computer vision.
Convolutional Neural Networks (CNN)
Object Detection in Images
Object Detection in Video

3.1 Speech Recognition

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

3.2 Project

Chatbot
Healthcare - Diagnostics with X Ray Data & Others across different domains

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