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AI+ Robotics (AI+ Robotics)

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5 Days
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    • T87377
    • 5 days
    • 06/09/2025 - 06/13/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
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    • T87378
    • 5 days
    • 07/14/2025 - 07/18/2025*
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    • T87379
    • 5 days
    • 08/18/2025 - 08/22/2025*
    • 9:00 AM
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    • Presented via WebEx
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    • T87380
    • 5 days
    • 09/15/2025 - 09/19/2025*
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    • T87381
    • 5 days
    • 10/20/2025 - 10/24/2025*
    • 9:00 AM
    • (GMT -05:00) Central Daylight Time
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Course Summary
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Description

Advance your expertise with the AI+ Robotics Training Program. This course equips robotics engineers with essential AI skills to enhance robotics applications, development, and integration. Join us today to lead the future of AI and robotics innovation.

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.

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.

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
  • AI+ Everyone

Who Should Attend

  • IT Professional
  • Robotics Engineer

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

Reinforcement Learning in Robotics

  • Basics of Reinforcement Learning (RL)
  • Implementing RL Algorithms for Robotics
  • Hands-on Session: Developing RL Models for Robots
  • Use-case: Optimizing Warehouse Operations with RL

Generative AI for Robotic Creativity

  • Exploring Generative AI: GANs and Applications
  • Creative Robots: Design, Creation, and Innovation
  • Hands-on Session: Generating Novel Designs for Robotics
  • Use-case: Custom Manufacturing with AI

Natural Language Processing (NLP) for Human-Robot Interaction

  • Introduction to NLP for Robotics
  • Voice-Activated Control Systems
  • Hands-on Session: Creating a Voice-command Robot Interface
  • Case-Study: Assistive Robots in Healthcare

Practical Activities and Use-Cases

  • Hands-on Session-1: Building AI Models for Object Recognition using Python Programming
  • Hands-on Session-2: Path Planning, Obstacle Avoidance, and Localization Implementation using Python Programming
  • Hands-on Session-3: PID Controller Implementation using Python programming
  • Use-cases: Precision Agriculture, Automated Assembly Lines

Emerging Technologies and Innovation in Robotics

  • Integration of Blockchain and Robotics
  • Quantum Computing and Its Potential

Exploring AI with Robotic Process Automation

  • Understanding Robotic Process Automation and its use cases
  • Popular RPA Tools and Their Features
  • Integrating AI with RPA

AI Ethics, Safety, and Policy

  • Ethical Considerations in AI and Robotics
  • Safety Standards for AI-Driven Robotics
  • Discussion: Navigating AI Policies and Regulations

Innovations and Future Trends in AI and Robotics

  • Latest Innovations in Robotics and AI
  • Future of Work and Society: Impact of AI and Robotics

Optional Module: AI Agents for Robotics

  • What Are AI Agents
  • Key Capabilities of AI Agents in Robotics
  • Applications and Trends for AI Agents in Robotics
  • How Does an AI Agent Work
  • Core Characteristics of AI Agents
  • The Future of AI Agents in Robotics
  • Types of AI Agents