Edge AI for Robots: TinyML, On-Device Inference & Optimization Training Course

This live, instructor-led training in Nigeria provides intermediate robotics engineers with practical expertise in autonomous navigation and SLAM via ROS 2. Participants will learn to integrate LiDAR sensors, apply mapping algorithms, run simulations in Gazebo, and deploy functional navigation stacks on real-world robotic hardware.

This instructor-led course in Nigeria focuses on robotics computer vision, utilizing OpenCV and deep learning technologies. Learners will master the implementation of perception pipelines, the integration of detection models, and the deployment of systems on embedded platforms to achieve autonomous control.

This instructor-led, live training in Nigeria (online or onsite) is designed for intermediate-level participants eager 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:

• Grasp the core principles of Human-Centric Physical AI and its real-world applications.
• Examine how collaborative robots contribute to enhancing workplace productivity.
• Recognize and tackle challenges associated with human-machine interactions.
• Develop workflows that optimize collaboration between humans and AI-driven systems.
• Foster a culture of innovation and adaptability in AI-integrated workplaces.

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

This hands-on training in Nigeria focuses on ROS-PLC integration and digital twins for 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.

This instructor-led live training in Nigeria (online or onsite) is designed for engineers who wish to explore the application of artificial intelligence to mechatronic systems.

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

• Gain a broad overview of artificial intelligence, machine learning, and computational intelligence.
• Understand the core concepts of neural networks and different learning methods.
• Effectively choose artificial intelligence approaches for solving real-life problems.
• Implement AI applications in mechatronic engineering.

An advanced training in Nigeria focusing on the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, implement distributed decision-making, and optimize agent collaboration through hands-on simulation in ROS 2 and Gazebo for practical applications.

This instructor-led, live training in Nigeria (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 instructor-led, live training in Nigeria (online or onsite) is tailored for intermediate-level participants looking to refine their expertise in designing, coding, and deploying intelligent robotic systems for automation and beyond.

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

• Comprehend the foundational principles of Physical AI and its role in robotics and automation.
• Design and program intelligent robotic systems suited for dynamic settings.
• Integrate AI models to facilitate autonomous decision-making in robots.
• Leverage simulation tools for rigorous robotic testing and optimization.
• Tackle technical challenges including sensor fusion, real-time processing, and energy efficiency.

This hands-on, instructor-led training in Nigeria focuses on rapid prototyping in robotics by leveraging ROS 2 and Docker. Participants will develop the ability to efficiently build, test, and deploy modular robotic systems, acquiring practical skills in containerization, simulation, and version control to support scalable development.

Offered in Nigeria, this instructor-led live training explores reinforcement learning principles and advanced deep RL techniques such as PPO and DDPG. Participants will implement algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to resolve complex operational tasks.

An advanced training in Nigeria focusing on deep learning for robotic manipulation. Discover perception, grasp planning, and control utilizing neural networks and ROS 2. Practical simulation exercises prepare you to successfully deploy intelligent, adaptable grasping solutions on physical robotic arms.