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AI+ Robotics

SS Course: 9000591

Course Overview

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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.                                                                  

Scheduled Classes

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08/18/25 - NVT - Virtual Classroom - Live Virtual (click to enroll)
09/15/25 - NVT - Virtual Classroom - Live Virtual (click to enroll)
10/20/25 - NVT - Virtual Classroom - Live Virtual (click to enroll)
11/17/25 - NVT - Virtual Classroom - Live Virtual (click to enroll)

What You'll Learn

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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.

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.
 

Outline

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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

Prerequisites

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  • 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.

    Who Should Attend

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    • IT Professional
    • Robotics Engineer

    Next Step Courses

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