Introduction to AI

Course Code

EAT-290

Duration

2 Days

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Target Audience

This course is designed for senior, middle, and high potential management who recognize that digital transformation and AI is unavoidable; and for those who understand that continuous improvement, innovation, and disruption is part of doing business and want to be prepared and reap the benefits of Artificial Intelligence.

Overview:

Artificial Intelligence (AI) is a field that has a long history but is still constantly and actively growing and changing. In this course, you will learn the basics of modern AI as well as some of the representative applications of AI.

Along the way, we also hope to excite you about the numerous applications and huge possibilities in the field of AI, which continue to expand the human capability beyond our imagination.

Course Objectives

By the end of the course, participants will be able to:

• Explain AI as a concept and all its applications.

• Apply the different AI applications in the business value chain.

• Demonstrate the technologies and algorithms behind AI.

• Assess the available and necessary skills and competencies.

• Discuss on a qualified level with business and data specialists on relevant topics.

Course Outline

Day One

Artificial Intelligence Definition

• Artificial Intelligence Definition

• Artificial Intelligence Types

• Examples

Gaming Inelegance

• Isolation Game

• Chess and strategic games intelligence

Historical overview of Artificial Intelligence

• Artificial Intelligence study research history

• Artificial Intelligence Factors

• Specifications of Artificial Intelligence

• Robotic Examples

Problems and Algorithms

• Reasoning, problem solving

• Knowledge representation

• Planning

• Learning

• Natural language processing

• Perception

• Motion and manipulation

• Social intelligence

• Creativity

• General intelligence

Approaches

• Cybernetics and brain simulation

• Symbolic

• Sub-symbolic

• Statistical

• Integrating the approaches

Tools

• Search and optimization

• Logic

• Probabilistic methods for uncertain reasoning

• Classifiers and statistical learning methods

• Artificial neural networks

• Languages

• Evaluating progress

Day Two

Existing Artificial Intelligence Apps

• AI tools for Personal use

• AI tools for Business use?—?Enterprise Intelligence

• AI tools for Business use?—?Enterprise Functions

• AI tools for Industry specific businesses

Artificial Intelligence Applications

• Machine Learning

• Expert Systems

• Computer Vision

• Natural Language Understanding

• Robotic

• Pattern Recognition

• Knowledge Management

• Automated Theorem Proving

Technical Overview Deep Learning & Artificial Neural Networks

• Apps made in Deep Learning & Artificial Neural Networks

• Historical look and improvements

• Examples of Deep Learning & Artificial Neural Networks

Artificial Intelligence Future

• Advantages of Artificial Intelligence

• Disadvantages of Artificial Intelligence

Philosophy and Ethics

• The limits of artificial general intelligence

• Potential risks and moral reasoning

• Machine consciousness, sentience, and mind

• Superintelligence