AI+ Robotics
The AI Robotics course covers the intersection of AI and robotics, focusing on creating intelligent, autonomous robotic systems through machine learning, computer vision, and real-time data processing.
All students receive:
- One-Year Subscription (with all updates)
- High-Quality E-Book
- Al Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Exam Study Guide
- Proctored Exam with one Free Retake
Check out our full list of training locations and learning formats. Please note that the location you choose may be an Established HD-ILT location with a virtual live instructor.
Train face-to-face with the live instructor.
Access to on-demand training content anytime, anywhere.
Attend the live class from the comfort of your home or office.
Interact with a live, remote instructor from a specialized, HD-equipped classroom near you. An SLI sales rep will confirm location availability prior to registration confirmation.
All Sunset Learning dates are guaranteed to run!
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Prerequisites:
Required:
- Familiarity with basic concepts of Artificial Intelligence (AI), without the need for technical expertise.
- Openness to generate innovative ideas and concepts, leveraging AI tools effectively in the process.
- Ability to analyze information critically and evaluate the implications of AI and Robotics technologies.
- Readiness to engage in problem-solving activities and apply AI techniques to real-world scenario.
Recommended:
- AI+ Executive or AI+ Everyone
Target Audience:
- Robotics Engineer
- IT Professional
Course Objectives:
- Gain a foundational understanding of robotics, including its history, evolution, and the role of AI in robotics.
- Explore and implement deep learning algorithms and reinforcement learning techniques in robotics applications.
- Develop practical skills through hands-on sessions and real-world case studies, focusing on autonomous systems and intelligent agents.
- Understand and apply ethical considerations, safety standards, and policy frameworks in AI-driven robotics.
- Stay updated on emerging trends and technologies shaping the future of AI and robotics.
Course Outline:
Introduction to Robotics and Artificial Intelligence (AI)
- Overview of Robotics: Introduction, History, Evolution, and Impact
- Introduction to Artificial Intelligence (AI) in Robotics
- Fundamentals of Machine Learning (ML) and Deep Learning
- Role of Neural Networks in Robotics
Understanding AI and Robotics Mechanics
- Components of AI Systems and Robotics
- Deep Dive into Sensors, Actuators, and Control Systems
- Exploring Machine Learning Algorithms in Robotics
Autonomous Systems and Intelligent Agents
- Introduction to Autonomous Systems
- Building Blocks of Intelligent Agents
- Case Studies: Autonomous Vehicles and Industrial Robots
- Key Platforms for Development: ROS (Robot Operating System)
AI and Robotics Development Frameworks
- Python for Robotics and Machine Learning
- TensorFlow and PyTorch for AI in Robotics
- Introduction to Other Essential Frameworks
Deep Learning Algorithms in Robotics
- Understanding Deep Learning: Neural Networks, CNNs
- Robotic Vision Systems: Object Detection, Recognition
- Hands-on Session: Training a CNN for Object Recognition
- Use-case: Precision Manufacturing with Robotic Vision