Artificial Intelligence and Machine Learning Courses

AI+ Robotics Practitioner - Self-paced

  • Length 365 days access
  • Inclusions Online exam
Course overview
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Why study this course

The AI+ Robotics Practitioner course is designed for robotics engineers, AI enthusiasts, technology professionals, and business leaders seeking to advance their expertise at the intersection of AI and robotics. The course delivers practical, industry-relevant capabilities that enable these professionals to design, develop, and optimise intelligent robotic systems, leveraging AI to drive innovation and automation across modern industries.

Throughout the course, learners will explore key areas including robotics fundamentals, deep learning and reinforcement learning techniques, autonomous systems, intelligent agents, and generative AI, supported by hands-on activities and real-world case studies. With a strong emphasis on practical application and ethical considerations, the course equips students with the experience to build and deploy AI-driven robotic solutions, while navigating governance, safety, and policy frameworks to enable responsible innovation.

Exam and certification

This course prepares students for the corresponding certification. The exam/assessment is completed online and provided as part of the course content.

The exam is:

  • 90 minutes

  • 50 multiple choice / multiple response questions

  • Pass mark is 35 out of 50 (i.e. 70%)

  • Online via AI Proctoring platform

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What you’ll learn

Through this course, students will be able to:

  • Acquire a comprehensive understanding of the symbiotic relationship between AI and Robotics.

  • Build proficiency in foundational Robotics and AI mechanics.

  • Advanced knowledge in DL algorithms and RL for Robotics applications.

  • Learn autonomous systems, intelligent agents, and generative AI.

  • Grasp ethical considerations and policy frameworks in AI.

  • Empower themselves to drive responsible innovation in the evolving AI and Robotics landscape.


AI CERTs Authorized Training Partner Platinum logo Oct 2025

AI CERTs at Lumify Work

AI CERTs® stands at the forefront of AI and blockchain certification, offering world-class programs that prepare individuals to lead in these rapidly growing fields. AI CERTs courses and certifications are vendor agnostic and designed to bridge the gap between theoretical knowledge and practical application, ensuring learners are equipped to make an immediate impact in their careers.
Lumify Work is a Platinum Authorized Training Partner for AI CERTs in Australia, New Zealand, and the Philippines.


Who is the course for?

This course is intended for:

  • Robotics Engineers

  • AI Enthusiasts

  • Technology Professionals

  • Business Leaders and Innovators


Course subjects

Module 1: 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

Module 2: 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

Module 3: 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)

Module 4: AI and Robotics Development Frameworks

  • Python for Robotics and Machine Learning

  • TensorFlow and PyTorch for AI in Robotics

  • Introduction to Other Essential Frameworks

Module 5: 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

Module 6: 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

Module 7: 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

Module 8: 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

Module 9: Practical Activities and Use Cases

  • Hands-on Session: Building AI Models for Object Recognition Using Python Programming

  • Hands-on Session: Path Planning, Obstacle Avoidance, and Localization Implementation Using Python Programming

  • Hands-on Session: PID Controller Implementation Using Python Programming

  • Use Cases: Precision Agriculture, Automated Assembly Lines

Module 10: Emerging Technologies and Innovation in Robotics

  • Integration of Blockchain and Robotics

  • Quantum Computing and Its Potential

Module 11: Exploring AI with Robotic Process Automation

  • Understanding Robotic Process Automation and Its Use Cases

  • Popular RPA Tools and Their Features

  • Integrating AI with RPA

Module 12: AI Ethics, Safety, and Policy

  • Ethical Considerations in AI and Robotics

  • Safety Standards for AI-Driven Robotics

  • Discussion: Navigating AI Policies and Regulations

Module 13: Innovations and Future Trends in AI and Robotics

  • Latest Innovations in Robotics and AI

  • Future of Work and Society: Impact of AI and Robotics

Additional 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


Prerequisites

  • Basic understanding of AI, Science, Technology, Engineering, or Mathematics (STEM), computer programming languages, mathematics, and physics.

  • Willingness to generate innovative ideas by effectively leveraging AI tools.

  • Ability to analyze information critically and evaluate the implications of AI and Robotics technologies.

  • Ready to engage in problem-solving activities and apply AI techniques to real-world scenarios.


Terms & Conditions

The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.


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