AI for Robotics Training in Prague

This practical, instructor-led training in Prague covers rapid prototyping for robotics using ROS 2 and Docker. Participants learn to build, test, and deploy modular robotic systems efficiently, gaining hands-on skills in containerization, simulation, and version control for scalable development.

This practical HRI course in Prague focuses on voice, gesture, and collaborative control. It guides you in building intuitive, multimodal interfaces for safe human-robot collaboration, with an emphasis on practical design principles, speech recognition, gesture detection, and shared autonomy to boost both usability and safety.

This practical training in Prague addresses ROS-PLC integration and digital twins within industrial automation. You will learn to synchronize robotic systems with PLCs, create digital replicas for simulation, and optimize production workflows via real-time data exchange and sophisticated monitoring methods.

An advanced training program on Prague focusing on deep learning for robotic manipulation. Master perception, grasp planning, and control using neural networks and ROS 2. Through hands-on simulation exercises, gain the skills to effectively deploy intelligent, adaptable grasping solutions on real robotic arms.

An advanced training module in Prague that covers the design and coordination of multi-robot systems. Learners will model swarm intelligence, implement distributed decision-making, and optimize inter-agent collaboration through hands-on simulations in ROS 2 and Gazebo, targeting practical real-world applications.

This instructor-led, live training in Prague equips advanced professionals with the skills to integrate TinyML into autonomous robotics. Participants will learn to design optimized models, implement on-device perception pipelines, and deploy lightweight AI on embedded hardware to achieve real-time autonomy.

This 21-hour, instructor-led training in Prague focuses on safety cases, verification, and explainable AI within robotics. It guides learners in applying hazard analysis, ethical governance, and compliance standards to ensure that robotic decision-making is transparent and trustworthy in real-world operational environments.

This live training in Prague supports intermediate engineers in deploying TinyML models for robotics. Learn to optimize inference for speed and energy, integrate AI into control systems, and create autonomous, low-latency robotic solutions directly on embedded hardware.

This instructor-led, live training in Prague (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 live, instructor-led training in Prague explores the core principles of reinforcement learning along with advanced deep RL techniques such as PPO and DDPG. Participants will gain practical skills in implementing algorithms using Python and PyTorch, integrating them with ROS 2 and OpenAI Gym, and training autonomous robots to tackle complex operational challenges.

This instructor-led training in Prague covers computer vision for robotics using OpenCV and deep learning. Participants will learn to implement perception pipelines, integrate detection models, and deploy systems on embedded platforms for autonomous control.

This instructor-led, live training in Prague (online or onsite) targets advanced robotics engineers and AI researchers looking to leverage Multimodal AI. The course focuses on integrating diverse sensory data to build more autonomous and efficient robots that can see, hear, and touch.

Upon completion of this training, participants will be able to:

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

This live, instructor-led training in Prague empowers intermediate-level robotics engineers with practical expertise in autonomous navigation and SLAM utilizing ROS 2. The curriculum guides learners through integrating LiDAR sensors, implementing advanced mapping algorithms, simulating scenarios in Gazebo, and deploying robust navigation stacks on real-world physical robots.

This live, instructor-led session in Prague (conducted online or on-site) is tailored for intermediate-level participants seeking to refine their skills in designing, programming, and deploying intelligent robotic systems for automation and beyond.

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

• Comprehend the fundamentals of Physical AI and its role in robotics and automation.
• Design and code intelligent robotic systems for dynamic environments.
• Implement AI models that facilitate autonomous decision-making in robots.
• Employ simulation tools to enhance robotic testing and optimization.
• Tackle key challenges, including sensor fusion, real-time processing, and energy efficiency.

This instructor-led live training in Prague (online or onsite) targets engineers interested in learning how artificial intelligence applies to mechatronic systems.

By the conclusion 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.