Artificial Intelligence : Introduction And Fundamentals

Artificial Intelligence : Introduction And Fundamentals, available at $19.99, with 41 lectures, and has 5 subscribers.

You will learn about This tutorial provides introductory knowledge on Artificial Intelligence. It would come to a great help if you are about to select Artificial Intelligence as a course subject. You can briefly know about the areas of AI. You will get a global view about AI This course is ideal for individuals who are This tutorial is prepared for the students at beginner level who aspire to learn Artificial Intelligence. It is particularly useful for This tutorial is prepared for the students at beginner level who aspire to learn Artificial Intelligence.

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Summary

Title: Artificial Intelligence : Introduction And Fundamentals

Price: $19.99

Number of Lectures: 41

Number of Published Lectures: 41

Number of Curriculum Items: 41

Number of Published Curriculum Objects: 41

Original Price: €19.99

Quality Status: approved

Status: Live

What You Will Learn

This tutorial provides introductory knowledge on Artificial Intelligence.
It would come to a great help if you are about to select Artificial Intelligence as a course subject.
You can briefly know about the areas of AI.
You will get a global view about AI

Who Should Attend

This tutorial is prepared for the students at beginner level who aspire to learn Artificial Intelligence.

Target Audiences

This tutorial is prepared for the students at beginner level who aspire to learn Artificial Intelligence.

‘I want to learn Artificial Intelligence . Where can I start?’

Say no more, you are in the very right place. This courses is a great introductorystep towards mastering Artificial intelligence.

The AI Technology is important because it helps software to undertake more easily, reliably and cheaply human skills learning, logic, preparation, connectivity and perception.

AI is critical because it solves a profound range of technological challenges effectively. More and more human qualities – machines, at low cost or at scale – can be applied – comprehension, logic, preparation, empathy and interpretation. General analytical activities that are carried out by software for several years, including identifying similarities in data, can also be done more reliably using AI.

In most business processes and customer applications, these capabilities generate new possibilities together.

There are other explanations for the need to learn AI than your work being redundant. Next, as people get new training in critical thought and humanities, occupations will change from dull, mundane ones to more imaginative ones. People would have to operate next to robots that have no artistic ability, so it would become paramount to use such logic. And thrilling!

We can’t forget AI and how necessary it is to be aware of it. I hope you will grasped in this course the fundamentals of AI.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Overview: What is Artificial Intelligence and its Philosophy

Lecture 2: Goals of Artificial Intelligence

Lecture 3: Applications of Artificial Intelligence

Chapter 2: Intelligent Systems

Lecture 1: History

Lecture 2: What is Intelligence and its types

Lecture 3: What does Intelligence Composed of?

Lecture 4: Difference between Human and Machine Intelligence

Lecture 5: Research Areas

Chapter 3: Agents and environment

Lecture 1: What are Agent and Environment?

Lecture 2: The nature of environments

Lecture 3: Agent Terminology

Lecture 4: What is Ideal rational Agent ?

Chapter 4: Popular Search Algorithms

Lecture 1: Single Agent Pathfinding Problems

Lecture 2: Brute-Force Search Strategies

Lecture 3: Comparison of Various Algorithms Complexities

Lecture 4: Local Search Algorithms

Chapter 5: Fuzzy Logic

Lecture 1: What is Fuzzy Logic?

Lecture 2: Membership Function

Lecture 3: Example of a Fuzzy Logic System

Lecture 4: Development

Chapter 6: Natural Language Processing

Lecture 1: Components of Natural Language Processing

Lecture 2: Steps in Natural Language Processing

Lecture 3: Implementation Aspects of Syntactic Analysis

Lecture 4: Natural Language Processing Terminorlogy

Chapter 7: Expert systems

Lecture 1: What are Expert Systems?

Lecture 2: Characteristics, Capabilities and Components of Expert Systems

Lecture 3: Limitations and Applications of expert systems

Lecture 4: Expert system technology

Lecture 5: Development of Expert Systems: General Steps

Chapter 8: Robotics

Lecture 1: What are Robots?

Lecture 2: Robot Locomotion

Lecture 3: Components of a Robot

Lecture 4: Computer Vision

Lecture 5: Applications of Robotics

Chapter 9: Artificial Neural Networks

Lecture 1: What are Artificial Neural Networks (ANNs)?

Lecture 2: Types of Artificial Neural Networks

Lecture 3: Working of Artificial neural networks

Lecture 4: Terminology

Lecture 5: Applications of Artificial neural networks

Lecture 6: Issues

Lecture 7: Terminology

Instructors

Fouzia Adjailia
Fou

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