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AI Data & Robotics

AI+ Robotics™

  • AI-Driven Robotics: Apply AI in Deep Learning, Reinforcement Learning, and smart automation
  • Real-World Systems: Work with autonomous systems and intelligent agents
  • Ethics & Innovation: Learn industry-aligned practices and innovation strategies
  • Hands-On Projects: Gain experience designing, optimising, and deploying robotics solutions

 


All prices are in NZD, ex GST (15%).

At a Glance: Course + Exam Overview

Category AI Data & Robotics
AI Technical
Program Name: AI+ Robotics™
Exam Format 50 questions, 70% passing, 90 Minutes Duration:
  • Instructor-Led: 5 Days
  • Self-Paced: 40 hours of content

🤝 You’re never on your own — Parasol Concierge Support provides integration guidance and expert VA assistance so you can focus on mastering skills while we handle the setup details.

WHAT You'll Learn

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.

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.

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.

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.

CERTIFICATION Modules

  • 1.1 Overview of Robotics: Introduction, History, Evolution, and Impact 
  • 1.2 Introduction to Artificial Intelligence (AI) in Robotics 
  • 1.3 Fundamentals of Machine Learning (ML) and Deep Learning 
  • 1.4 Role of Neural Networks in Robotics 

  • 2.1 Components of AI Systems and Robotics 
  • 2.2 Deep Dive into Sensors, Actuators, and Control Systems 
  • 2.3 Exploring Machine Learning Algorithms in Robotics

  • 3.1 Introduction to Autonomous Systems 
  • 3.2 Building Blocks of Intelligent Agents 
  • 3.3 Case Studies: Autonomous Vehicles and Industrial Robots 
  • 3.4 Key Platforms for Development: ROS (Robot Operating System) 

  • 4.1 Python for Robotics and Machine Learning 
  • 4.2 TensorFlow and PyTorch for AI in Robotics 
  • 4.3 Introduction to Other Essential Frameworks 

  • 5.1 Understanding Deep Learning: Neural Networks, CNNs 
  • 5.2 Robotic Vision Systems: Object Detection, Recognition 
  • 5.3 Hands-on Session: Training a CNN for Object Recognition 
  • 5.4 Use-case: Precision Manufacturing with Robotic Vision 

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

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

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

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

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

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

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

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

  1. 1. What Are AI Agents
  2. 2. Key Capabilities of AI Agents in Robotics
  3. 3. Applications and Trends for AI Agents in Robotics
  4. 4. How Does an AI Agent Work
  5. 5. Core Characteristics of AI Agents
  6. 6. The Future of AI Agents in Robotics
  7. 7. Types of AI Agents

Industry opportunities

AI Robotics Integration Expert:

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

AI Robotics System Developer:

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

Robotics Engineer with AI Expertise:

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

AI Intelligent Robotics Specialist:

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

FREQUENTLY ASKED QUESTIONS

The AI+ Robotics™ Certification provides a comprehensive understanding of the intersection of Artificial Intelligence (AI) and Robotics.

This certification is ideal for professionals and enthusiasts interested in AI and Robotics, including those with basic familiarity with AI concepts.

You will gain hands-on experience in building AI models, training neural networks, developing reinforcement learning models.

This certification will enhance your skills in AI and Robotics, making you a valuable asset in industries adopting automation and AI-driven solutions.

Participants should have a basic understanding of AI concepts, be open to generating innovative ideas, have the ability to critically analyze information.

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

EXAM DETAILS

Duration

90 Minutes

Passing Score

70%

Format

50 multiple-choice/multiple-response questions

EXAM BLUEPRINT

Introduction to Robotics and Artificial Intelligence (AI) 5%
Understanding AI and Robotics Mechanics 6%
Autonomous Systems and Intelligent Agents 6%
AI and Robotics Development Frameworks 9%
Deep Learning Algorithms in Robotics 9%
Reinforcement Learning in Robotics 9%
Generative AI for Robotic Creativity 9%
Natural Language Processing (NLP) for Human-Robot Interaction 9%
Practical Activities and Use-Cases 8%
Emerging Technologies and Innovation in Robotics 9%
Exploring AI with Robotic Process Automation (RPA) 9%
AI Ethics, Safety, and Policy 6%
Innovations and Future Trends in AI and Robotics 6%

Instructor-Led (Live Virtual/Classroom)

  • 5 days of intensive training with live demos
  • Real-time Q&A, peer collaboration, and hands-on labs
  • Led by AI Certified Trainers and delivered through Authorized Training Partners

Instructor-Led Course

🚀 Learn directly from certified AI trainers in live, interactive sessions. Get real-time guidance, practical exercises, and the accountability of a structured classroom experience. Perfect for professionals who want expert support and a clear path to certification.

✨ At Parasol Virtual, we go beyond certification. Our team supports your learning journey with guidance, resources, and local assistance to ensure your success. You’re not learning alone — you’re part of a global community with local support.

Request Virtual Training

Self-Paced Online

  • ~30 hours of on-demand video lessons, e-book, podcasts, and interactive labs
  • Learn anywhere, anytime, with modular quizzes to track progress

Self-Paced Course

🌐 Study anytime, anywhere with 24/7 access to course materials, practice tests, and resources. Move at your own speed while still working towards globally recognized certification. Designed for busy learners who value flexibility without compromising quality.

✨ At Parasol Virtual, we go beyond certification. Our team supports your learning journey with guidance, resources, and local assistance to ensure your success. You’re not learning alone — you’re part of a global community with local support.

Purchase Self-Paced Course

TECHNOLOGIES USED

OpenAI Gym
OpenAI Gym
GreyOrange
GreyOrange
Neurala
Neurala
Dialogflow
Dialogflow