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AI+ Robotics™

AT-420

Build the Future with Smart Automation

The AI+ Robotics certification program offers a transformative journey into the dynamic intersection of Artificial Intelligence (AI) and Robotics. From foundational concepts to advanced Deep Learning algorithms and Reinforcement Learning, the immersive experience is tailored for Robotics applications. Each module provides a well-rounded understanding, exploring autonomous systems, intelligent agents, and generative AI. Through hands-on activities and real world case studies, practical skills are honed. Ethical considerations and policy frameworks are navigated responsibly. Stay updated on emerging trends, shaping the future of the industry. By the program's end, acquire both robust theoretical knowledge and practical expertise, empowering you to lead innovation in the ever-evolving AI and Robotics landscape.

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Prerequisites

  • 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

Modules

13

Examination

1

50 MCQs

90 Minutes

Passing Score

70%

Certification Modules

  1. 1.1 Overview of Robotics: Introduction, History, Evolution, and Impact
  2. 1.2 Introduction to Artificial Intelligence (AI) in Robotics
  3. 1.3 Fundamentals of Machine Learning (ML) and Deep Learning
  4. 1.4 Role of Neural Networks in Robotics
  1. 2.1 Components of AI Systems and Robotics
  2. 2.2 Deep Dive into Sensors, Actuators, and Control Systems
  3. 2.3 Exploring Machine Learning Algorithms in Robotics
  1. 3.1 Introduction to Autonomous Systems
  2. 3.2 Building Blocks of Intelligent Agents
  3. 3.3 Case Studies: Autonomous Vehicles and Industrial Robots
  4. 3.4 Key Platforms for Development: ROS (Robot Operating System)
  1. 4.1 Python for Robotics and Machine Learning
  2. 4.2 TensorFlow and PyTorch for AI in Robotics
  3. 4.3 Introduction to Other Essential Frameworks
  1. 5.1 Understanding Deep Learning: Neural Networks, CNNs
  2. 5.2 Robotic Vision Systems: Object Detection, Recognition
  3. 5.3 Hands-on Session: Training a CNN for Object Recognition
  4. 5.4 Use-case: Precision Manufacturing with Robotic Vision
  1. 6.1 Basics of Reinforcement Learning (RL)
  2. 6.2 Implementing RL Algorithms for Robotics
  3. 6.3 Hands-on Session: Developing RL Models for Robots
  4. 6.4 Use-case: Optimizing Warehouse Operations with RL
  1. 7.1 Exploring Generative AI: GANs and Applications
  2. 7.2 Creative Robots: Design, Creation, and Innovation
  3. 7.3 Hands-on Session: Generating Novel Designs for Robotics
  4. 7.4 Use-case: Custom Manufacturing with AI
  1. 8.1 Introduction to NLP for Robotics
  2. 8.2 Voice-Activated Control Systems
  3. 8.3 Hands-on Session: Creating a Voice-command Robot Interface
  4. 8.4 Case-Study: Assistive Robots in Healthcare
  1. 9.1 Hands-on Session-1: Building AI Models for Object Recognition using Python Programming
  2. 9.2 Hands-on Session-2: Path Planning, Obstacle Avoidance, and Localization Implementation using Python Programming
  3. 9.3 Hands-on Session-3: PID Controller Implementation using Python programming
  4. 9.4 Use-cases: Precision Agriculture, Automated Assembly Lines
  1. 10.1 Integration of Blockchain and Robotics
  2. 10.2 Quantum Computing and Its Potential
  1. 11.1 Understanding Robotic Process Automation and its use cases
  2. 11.2 Popular RPA Tools and Their Features
  3. 11.3 Integrating AI with RPA
  1. 12.1 Ethical Considerations in AI and Robotics
  2. 12.2 Safety Standards for AI-Driven Robotics
  3. 12.3 Discussion: Navigating AI Policies and Regulations
  1. 13.1 Latest Innovations in Robotics and AI
  2. 13.2 Future of Work and Society: Impact of AI and Robotics

Certification Modules

  1. 1.1 Overview of Robotics: Introduction, History, Evolution, and Impact
  2. 1.2 Introduction to Artificial Intelligence (AI) in Robotics
  3. 1.3 Fundamentals of Machine Learning (ML) and Deep Learning
  4. 1.4 Role of Neural Networks in Robotics
  1. 2.1 Components of AI Systems and Robotics
  2. 2.2 Deep Dive into Sensors, Actuators, and Control Systems
  3. 2.3 Exploring Machine Learning Algorithms in Robotics
  1. 3.1 Introduction to Autonomous Systems
  2. 3.2 Building Blocks of Intelligent Agents
  3. 3.3 Case Studies: Autonomous Vehicles and Industrial Robots
  4. 3.4 Key Platforms for Development: ROS (Robot Operating System)
  1. 4.1 Python for Robotics and Machine Learning
  2. 4.2 TensorFlow and PyTorch for AI in Robotics
  3. 4.3 Introduction to Other Essential Frameworks
  1. 5.1 Understanding Deep Learning: Neural Networks, CNNs
  2. 5.2 Robotic Vision Systems: Object Detection, Recognition
  3. 5.3 Hands-on Session: Training a CNN for Object Recognition
  4. 5.4 Use-case: Precision Manufacturing with Robotic Vision
  1. 6.1 Basics of Reinforcement Learning (RL)
  2. 6.2 Implementing RL Algorithms for Robotics
  3. 6.3 Hands-on Session: Developing RL Models for Robots
  4. 6.4 Use-case: Optimizing Warehouse Operations with RL
  1. 7.1 Exploring Generative AI: GANs and Applications
  2. 7.2 Creative Robots: Design, Creation, and Innovation
  3. 7.3 Hands-on Session: Generating Novel Designs for Robotics
  4. 7.4 Use-case: Custom Manufacturing with AI
  1. 8.1 Introduction to NLP for Robotics
  2. 8.2 Voice-Activated Control Systems
  3. 8.3 Hands-on Session: Creating a Voice-command Robot Interface
  4. 8.4 Case-Study: Assistive Robots in Healthcare
  1. 9.1 Hands-on Session-1: Building AI Models for Object Recognition using Python Programming
  2. 9.2 Hands-on Session-2: Path Planning, Obstacle Avoidance, and Localization Implementation using Python Programming
  3. 9.3 Hands-on Session-3: PID Controller Implementation using Python programming
  4. 9.4 Use-cases: Precision Agriculture, Automated Assembly Lines
  1. 10.1 Integration of Blockchain and Robotics
  2. 10.2 Quantum Computing and Its Potential
  1. 11.1 Understanding Robotic Process Automation and its use cases
  2. 11.2 Popular RPA Tools and Their Features
  3. 11.3 Integrating AI with RPA
  1. 12.1 Ethical Considerations in AI and Robotics
  2. 12.2 Safety Standards for AI-Driven Robotics
  3. 12.3 Discussion: Navigating AI Policies and Regulations
  1. 13.1 Latest Innovations in Robotics and AI
  2. 13.2 Future of Work and Society: Impact of AI and Robotics

Exam Objectives

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Algorithm Development and Implementation

Developing the ability to implement deep learning and reinforcement learning algorithms specifically tailored for robotics, equipping learners with the skills to create intelligent and adaptive robotic behaviors.

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Human-Robot Interaction and Communication

Gaining expertise in Natural Language Processing (NLP) for facilitating effective human-robot interaction, enhancing the ability of robots to understand and respond to human commands and communications.

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Generative AI for Creative Applications

Learning to apply generative AI techniques for enhancing robotic creativity, allowing robots to generate novel solutions and approaches in various tasks and problem-solving scenarios.

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Practical Application and Use-Case Implementation

Developing hands-on experience through practical activities and real-world use-cases, which reinforces theoretical knowledge and provides learners with the skills to apply their learning to actual robotic projects and challenges.

Career Opportunities Post-Certification

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Median Salaries

$59,391
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With AI Skills

$130,558
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% Difference

120
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Robotics Engineer with AI Expertise

Designs and develops advanced robots, integrating AI algorithms to enhance autonomy, decision-making, and overall robotic functionality.

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AI Robotics System Developer

Creates complex robotic systems incorporating AI, focusing on enhancing capabilities like perception, learning, and adaptive behavior.

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AI Intelligent Robotics Specialist

Specializes in developing intelligent robots that utilize AI for advanced tasks, such as navigation, manipulation, and human interaction.

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AI Robotics Integration Expert

Integrates AI technologies into existing robotic systems, enhancing their performance and enabling new functionalities and applications.

Hear it from the Learners

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Marc H

Happy to share I've completed the AI+ Executive Certification from AI CERTs! This program has sharpened my skills in strategic AI application + implementation, further equipping me to lead AI-driven organizational transformation.

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Georgia L

As VP Operations, my recent completion of the AI+ Executive exam through AI CERTs was a pivotal step in advancing my AI skill set as we embrace an AI-driven future. This certification not only deepened my understanding of AI's broad impact across various divisions but also equipped me with the tools to make informed, strategic decisions.

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Antonio C

AI+ Executive™ Instructor Guide Certificate. Today, I am part of the team of #CompuEducación instructors to teach the #AI CERTs AI+Executive certification course . This 8-hour course is a new standard for business leaders who want to start a solid path in the adoption of AI for the transformation of their companies. The technological, business, ethical, legal and strategy foundations are covered. The examples of using “AI” are practical, up-to-date, and touch on the different variants of “AI.”

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Doug F

Excited to successfully complete AI Cert's AI+ Marketing certification course! For us marketers, it's imperative to embrace AI and take an active effort in learning how to harness its capabilities to stay relevant and be on the cutting edge of tech.

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Frequently Asked Questions

The AI+ Robotics Certification is an immersive educational experience designed to provide a comprehensive understanding of the intersection of Artificial Intelligence (AI) and Robotics. It covers foundational concepts, advanced algorithms, hands-on activities, and real-world case studies.

This certification is ideal for professionals and enthusiasts interested in AI and Robotics, including those with basic familiarity with AI concepts but no need for technical expertise. It is suitable for individuals looking to innovate and apply AI techniques to real-world scenarios.

You will gain hands-on experience in building AI models, training neural networks, developing reinforcement learning models, creating voice-command interfaces, and implementing various robotics use-cases.

The certification will enhance your skills in AI and Robotics, making you a valuable asset in industries that are increasingly adopting automation and AI-driven solutions. It positions you to lead innovation and stay ahead in a rapidly evolving technological landscape.

Participants should have a basic understanding of AI concepts, be open to generating innovative ideas, have the ability to critically analyze information, and be ready to engage in problem-solving activities.

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