Course Outline
Introduction
Overview of Artificial Intelligence (AI)
- Machine learning
- Computational intelligence
Understanding Neural Network Concepts
- Generative networks
- Deep neural networks
- Convolutional neural networks
Understanding Various Learning Methods
- Supervised learning
- Unsupervised learning
- Reinforcement learning
- Semi-supervised learning
Other Computational Intelligence Algorithms
- Fuzzy systems
- Evolutionary algorithms
Exploring AI Approaches to Optimization
- Selecting AI Approaches Effectively
Learning about Stochastic Dynamic Programming
- Relationship with AI
Implementing Mechatronic Applications with AI
- Medicine
- Rescue operations
- Defense
- Industry-agnostic trends
Case Study: The Intelligent Robotic Car
Programming the Major Systems of a Robot
- Project Planning
Implementing AI Capabilities
- Search and Motion Control
- Localization and Mapping
- Tracking and Control
Summary and Next Steps
Requirements
- A foundational understanding of computer science and engineering principles.
Target Audience
- Engineers
Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
