AI for Robotics Training in Durban

This practical, instructor-led training in Durban focuses on rapid prototyping in robotics using ROS 2 and Docker. Learners will develop the ability to build, test, and deploy modular robotic systems with efficiency, acquiring practical skills in containerisation, simulation, and version control to support scalable development.

This hands-on HRI course in Durban explores voice, gesture, and collaborative control. Participants will learn to build intuitive, multimodal interfaces for safe human-robot collaboration, with a strong emphasis on practical design principles, speech recognition, gesture detection, and shared autonomy to boost usability and safety.

This practical training in Durban addresses ROS-PLC integration and digital twins within industrial automation. Participants will learn to synchronize robotic systems with PLCs, develop digital replicas for simulation purposes, and optimize production workflows through real-time data exchange and advanced monitoring techniques.

An advanced training programme in Durban focused on deep learning for robotic manipulation. Master perception, grasp planning, and control using neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent, adaptable grasping solutions on real robotic arms.

An advanced course in Durban that covers the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and optimise collaboration across agents through hands-on simulation using ROS 2 and Gazebo, preparing them for real-world applications.

This instructor-led, live training in Durban teaches advanced professionals how to integrate TinyML into autonomous robotics. Participants will design optimised models, implement on-device perception pipelines, and deploy lightweight AI on embedded hardware for real-time autonomy.

This 21-hour instructor-led programme on Durban delves into safety cases, verification, and explainable AI for robotics. It equips learners to apply hazard analysis, ethical governance, and compliance standards to guarantee transparent and trustworthy robotic decision-making in real-world settings.

This live training in Durban guides intermediate engineers in deploying TinyML models for robotics. You will learn to optimise inference for speed and energy efficiency, integrate AI into control systems, and build autonomous, low-latency robotic solutions directly on embedded hardware.

This instructor-led, live training in Durban (online or onsite) is aimed at intermediate-level participants who wish to explore the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces.

By the end of this training, participants will be able to:

• Understand the principles of Human-Centric Physical AI and its applications.
• Explore the role of collaborative robots in enhancing workplace productivity.
• Identify and address challenges in human-machine interactions.
• Design workflows that optimize collaboration between humans and AI-driven systems.
• Promote a culture of innovation and adaptability in AI-integrated workplaces.

This guided live training in Durban explores the core principles of reinforcement learning alongside advanced deep RL methods such as PPO and DDPG. Learners will develop algorithms using Python and PyTorch, integrate these with ROS 2 and OpenAI Gym, and train autonomous robots to tackle complex operational challenges.

This instructor-led training in Durban focuses on applying computer vision to robotics through OpenCV and deep learning. Learners will develop the skills to build perception pipelines, integrate detection models, and deploy systems on embedded platforms to facilitate autonomous control.

This instructor-led, live training in Durban (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.

By the end of this training, participants will be able to:

• Implement multimodal sensing in robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Create robots that can perform complex tasks in dynamic environments.
• Address challenges in real-time data processing and actuation.

This live, instructor-led training in Durban provides intermediate robotics engineers with practical skills in autonomous navigation and SLAM using ROS 2. You will learn to integrate LiDAR sensors, implement mapping algorithms, run simulations in Gazebo, and deploy navigation stacks on physical robots for real-world applications.

This instructor-led live training in Durban, available either online or onsite, is tailored for intermediate-level participants seeking to advance their skills in designing, programming, and deploying intelligent robotic systems for automation and broader applications.

By the end of the course, participants will be able to:

• Grasp the core principles of Physical AI and its relevance to robotics and automation.
• Design and program intelligent robotic systems suited for dynamic environments.
• Implement AI models that enable autonomous decision-making in robots.
• Apply simulation tools for rigorous robotic testing and optimization.
• Tackle critical challenges such as sensor fusion, real-time processing, and energy efficiency.

This instructor-led, live training in Durban (online or onsite) is designed for engineers who wish to learn about the applicability of artificial intelligence to mechatronic systems.

By the end of this training, participants will be able to:

• Gain an overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the concepts of neural networks and different learning methods.
• Choose artificial intelligence approaches effectively for real-life problems.
• Implement AI applications in mechatronic engineering.