Artifical Intelligance

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OVERVIEW

Job Roles Available

  • Machine learning engineer
  • Data scientist
  • Research scientist
  • Business intelligence developer
  • Computer vision engineer

Who to Join

  • Graduates
  • Post Graduates
  • IT Professionals
  • Data Analysts, Business Analysts
  • Python Professionals
  • Also, anyone having interest to learn Artificial Intelligence

Why Artificial Intelligence ?

  1. To Create Expert Systems: The systems which exhibit intelligent behavior, learn, demonstrate, explain, and advice its users.
  2. To Implement Human Intelligence in Machines: Creating systems that understand, think, learn, and behave like humans.
  3. The goal of AI is to develop computers that can simulate the ability to think, as well as see, hear, walk, talk, and feel.

Real Life Applications of AI

  1. Expert Systems

The expert systems are the computer applications developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise.

Examples: Flight-tracking systems, Clinical systems

  1. Natural Language Processing

Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems using a natural language such as English.

Examples: Google Now feature, speech recognition, Automatic voice output

  1. Neural Networks Examples

Yet another research area in AI, neural networks, is inspired from the natural neural network of human nervous system.

Examples: Pattern recognition systems such as face recognition, character recognition, handwriting recognition.

  1. Robotics

Robotics is a branch of AI, which is composed of Electrical Engineering, Mechanical Engineering, and Computer Science for designing, construction, and application of robots.

Examples: Industrial robots for moving, spraying, painting, precision checking, drilling, cleaning, coating, carving etc.

5. Fuzzy Logic

Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning. The approach of FL imitates the way of decision making in humans that involves all intermediate possibilities between digital values YES and NO.

COURSE MAP

Course Overview

  • Deep Learning
  • Robotics
  • Natural Language Processing
  • Reinforcement Learning
  • Artificial Neural Network
  • Expert Systems
  • Fuzzy Systems
  • Computer Vision

Machine Learning: Ensemble Techniques

  • Boosting and Bagging
  • Random Forests

Machine Learning: Reinforcement Learning

  • Value-based methods (e.g. Q-learning)
  • Policy-based methods

Deep Learning

  • Neural Network Basics
  • Deep Neural Networks
  • Recurrent Neural Networks (RNN)
  • Deep Learning applied to Images using CNN
  • Tensor Flow for Neural Networks & Deep Learning

Machine Learning: Unsupervised Learning

  • Clustering (k-means, hierarchical, high-dimensional)
  • Expectation Maximization

Neural Networks

  • Introduction To Machine Learning & Neural Nets
  • Neural Network Architecture
  • Object Recognition With Neural Nets
  • Recurrent Neural Networks

Expert Systems

  • User Interface
  • Inference Engine
  • Knowledge Base

Fuzzy Logic

  • Fuzzification Module
  • Knowledge Base
  • Inference Engine
  • Defuzzification Module

Computer Vision

  • Convolutional Neural Networks
  • Keras library for deep learning in Python
  • Pre-processing Image Data
  • Object & face recognition using techniques above

Projects

  • Handwriting Detection
  • Sentiment Analysis on Amazon Food Review
  • Image Identification
  • Employee Exit Prediction

CERTIFICATION

GET CERTIFICATION AFTER THE ASSESSMENT TEST CLEARED

FEES

Fees

 
Application Fees INR 0
Total Program Fees INR 35,000
The Program Fees can also be paid in installments
Registration  Fees INR5000(Nonrefundable)
First installment of the Program Fees

(Needs to Paid One Week Before the Batch Start Date)

 INR 15,000
Second installment of the Program Fees

(Needs To Be Paid in the 6th Class)

 INR 15,000
Discount on Program Fees: 10% Early Bird Discount valid till 10/02/19

10%  Extra discount on Lumsum Payment

Batch Closed:             27th Jan 2019

New Batch Starting:  15th Feb 2019 (Few Seats Left)

2nd Batch:                   01st March 2019
Admission Open Till: 10th Feb 2019 ( If Required Seats Filled, the admissions will be closed even before the Closing Date)
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