This course aims at providing the participants with the skills and knowledge about artificial intelligence, its fields and the applications used in to reach effective, sound, appropriate and supportive decisions for the technical and administrative work environment.

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

·         Recognize the concept of Artificial intelligence, its reality and future, and identify its advantages.

·         Differentiate between AI & Learning machine.

·         Recognize the skill of dealing with Artificial intelligence programs.

·         Be familiar with the areas of Artificial Intelligence.

·         Learn about the systems and applications of artificial intelligence and expert systems in the areas of business environments and project management.

Course Curriculum

9 Lectures
Module 1 - Technological Revolution – Overview
  • Technological Revolution Timeline
  • AI in Our Everyday Lives
  • Data volumes driving AI
  • What is Artificial Intelligence?
  • Goals of AI
  • What Contributes to AI?
  • What is AI Technique?
  • Applications of AI
Module 2 - What is Intelligent?
  • History of AI
  • What is Intelligence?
  • Types of Intelligence
  • Difference between Human and Machine Intelligence
  • Research Areas of AI
  • Real Life Applications of Research Areas
  • Task Classification of AI
Module 3 - Agents and environments
  • What are Agents and Environment?
  • Agents Terminology
  • What is Ideal Rational Agent?
  • The Structure of Intelligent Agents
  • Local Search Algorithms
Module 4 - The Fuzzy Logic Systems and Natural Language Processing
  • What is Fuzzy Logic?
  • Implementation
  • Fuzzy Logic Systems Architecture
  • Membership Functions
  • Example of a Fuzzy Logic System
  • Application Areas of Fuzzy Logic
  • The key application areas of fuzzy logic
  • Advantages & Disadvantages of FLSs
  • Natural language processing
Module 5 - Expert systems
  • What are Expert Systems?
  • Characteristics of Expert Systems:
  • The expert systems are capable of:
  • Components of Expert Systems:
  • Applications of Expert System
  • Expert System Technology
  • Development of Expert Systems
  • Benefits of Expert Systems
Module 6 - Robotics
  • What are Robots?
  • Aspects of Robotics
  • Difference in Robot System and Other AI Program
  • Robot, Legged, Wheeled & Slip/Skid Locomotion
  • Components of a Robot
  • Hardware & tasks of Computer Vision System
  • Applications of Robotics
Module 7 - Neural networks
  • What are Artificial Neural Networks (ANNs)?
  • Basic Structure of ANNs
  • Types of Artificial Neural Networks
  • Machine Learning in ANNs
  • Bayesian Networks (BN)
  • Multi-class Logistic Regression
  • Robotics Process Automation
Module 8 - Digital Transformation Journey
  • Automation Market View
  • CoE-Based Service Delivery Organization
  • CoE-Based Delivery Framework
  • RPA Center of Excellence
  • RPA Service Delivery Approach
  • RPA Help Desk & Production Support
Module 9 - Robotic process automation
  • What is Robotics Process Automation
  • Roadmap to implement RPA
  • Example of RPA

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