Course Outline

Introduction

Overview of Artificial Intelligence (AI)

  • Machine learning
  • Computational intelligence

Understanding the Concepts of Neural Networks

  • Generative networks
  • Deep neural networks
  • Convolution neural networks

Understanding Various Learning Methods

  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
  • Semi-supervised learning

Other Computational Intelligence Algorithms

  • Fuzzy systems
  • Evolutionary algorithms

Exploring Artificial Intelligence Approaches to Optimization

  • Choosing AI Approaches Effectively

Learning about Stochastic Dynamic Programming

  • Relationship with AI

Implementing Mechatronic Applications with AI

  • Medicine
  • Rescue
  • Defense
  • Industry-agnostic trend

Case Study: The Intelligent Robotic Car

Programming the Major Systems of a Robot

  • Planning the Project

Implementing AI Capabilities

  • Searching and Motion Control
  • Localization and Mapping
  • Tracking and Controlling

Summary and Next Steps

Requirements

  • Basic understanding of computer science and engineering

Audience

  • Engineers
 21 Hours

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