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

This live, instructor-led training held in Kenya provides mid-level robotics engineers with practical expertise in autonomous navigation and SLAM through ROS 2. The curriculum covers integrating LiDAR sensors, applying mapping algorithms, simulating scenarios in Gazebo, and deploying functional navigation stacks on physical robots.

This instructor-led training on Kenya explores computer vision for robotics, leveraging OpenCV and deep learning. Participants will master the implementation of perception pipelines, integration of detection models, and deployment of systems on embedded platforms to achieve autonomous control.

This guided, live training in Kenya (available online or onsite) targets intermediate-level participants interested in exploring the impact of collaborative robots (cobots) and other human-centric AI systems on contemporary workplaces.

Upon completing this training, learners will be equipped to:

• Grasp the core principles of Human-Centric Physical AI and their practical applications.
• Examine how collaborative robots contribute to improved workplace efficiency.
• Recognize and resolve issues arising from human-machine interactions.
• Create workflows that maximize the synergy between humans and AI-driven systems.
• Foster a workplace culture that values innovation and adaptability in AI-integrated environments.

This practical HRI course in Kenya focuses on voice, gesture, and collaborative control. You will learn to construct intuitive, multimodal interfaces that facilitate safe human-robot collaboration. The curriculum emphasizes practical design principles, speech recognition, gesture detection, and shared autonomy to bolster both usability and safety.

This hands-on training in Kenya covers ROS-PLC integration and digital twins for industrial automation. Learn to synchronize robotic systems with PLCs, create digital replicas for simulation, and enhance production workflows through real-time data exchange and advanced monitoring techniques.

This instructor-led live training in Kenya (online or onsite) is designed for engineers who want to explore how artificial intelligence can be applied to mechatronic systems.

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

• Obtain an overview of artificial intelligence, machine learning, and computational intelligence.
• Grasp the concepts of neural networks and various learning methods.
• Select the most effective AI approaches for addressing real-world problems.
• Implement AI applications within mechatronic engineering.

An advanced course in Kenya focused on the design and coordination of multi-robot systems. Learners will develop the skills to model swarm intelligence, implement distributed decision-making, and optimize inter-agent collaboration through hands-on simulation using ROS 2 and Gazebo, readying them for practical applications.

This instructor-led, live training in Kenya (online or onsite) is designed for advanced robotics engineers and AI researchers eager to harness Multimodal AI to integrate diverse sensory data, thereby creating robots that are more autonomous, efficient, and capable of seeing, hearing, and touching.

Upon completing this training, participants will be equipped to:

• Implement multimodal sensing within robotic systems.
• Develop AI algorithms for sensor fusion and decision-making processes.
• Build robots capable of executing complex tasks in dynamic environments.
• Tackle challenges associated with real-time data processing and actuation.

This instructor-led, live training on Kenya (available online or onsite) targets intermediate-level professionals seeking to sharpen their capabilities in designing, programming, and deploying intelligent robotic systems for automation and broader applications.

Upon completion, participants will be able to:

• Comprehend the fundamental 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 facilitate autonomous decision-making in robotic systems.
• Employ simulation tools to streamline robotic testing and optimization processes.
• Resolve key technical challenges such as sensor fusion, real-time processing, and energy efficiency.

This practical, instructor-led training in Kenya focuses on rapid prototyping for robotics utilizing ROS 2 and Docker. Participants will learn to efficiently build, test, and deploy modular robotic systems, acquiring hands-on expertise in containerization, simulation, and version control to support scalable development.

This instructor-led live session in Kenya focuses on the core principles of reinforcement learning and advanced deep RL techniques such as PPO and DDPG. Participants will apply these algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and guide autonomous robots in solving intricate tasks.

An advanced training on Kenya that covers deep learning applications in robotic manipulation. Acquire skills in perception, grasp planning, and control using neural networks and ROS 2. Through hands-on simulation exercises, you will be prepared to effectively deploy intelligent and adaptable grasping solutions on real robotic arms.