Physical AI for Robotics and Automation Training Course

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate-level participants interested in the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces.

By the conclusion of this course, participants will be able to:

• Comprehend the foundational principles of Human-Centric Physical AI and its real-world applications.
• Analyze the contribution of collaborative robots to workplace productivity.
• Identify and mitigate challenges in human-machine interactions.
• Develop workflows that optimize collaboration between humans and AI-driven systems.
• Cultivate a culture of innovation and adaptability within AI-integrated workplaces.

This practical HRI module in Turkey focuses on voice, gesture, and collaborative control. Discover how to build intuitive, multimodal interfaces that facilitate safe human-robot collaboration. The content prioritizes applied design principles, speech recognition, gesture detection, and shared autonomy to bolster both usability and safety.

This hands-on training in Turkey addresses ROS-PLC integration and digital twins for industrial automation. Learners will master the synchronization of robotic systems with PLCs, the development of digital replicas for simulation, and the optimization of production workflows via real-time data exchange and advanced monitoring techniques.

This instructor-led live training in Turkey (offered online or on-site) targets engineers interested in applying artificial intelligence to mechatronic systems.

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

• Gain a broad overview of artificial intelligence, machine learning, and computational intelligence.
• Understand neural network concepts and diverse learning methods.
• Select suitable artificial intelligence approaches for solving real-world problems.
• Implement AI applications in mechatronic engineering.

This instructor-led, live training in Turkey (online or onsite) targets advanced robotics engineers and AI researchers seeking to leverage Multimodal AI to integrate diverse sensory data. The goal is to build more autonomous and efficient robots capable of seeing, hearing, and touching.

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.
• Create robots capable of executing complex tasks in dynamic environments.
• Tackle challenges related to real-time data processing and actuation.

This practical, instructor-led course in Turkey focuses on rapid prototyping for robotics through the integration of ROS 2 and Docker. Learners will develop the proficiency to efficiently build, test, and scale modular robotic systems, gaining practical experience in containerization, simulation, and version control for sustainable development.

An advanced training in Turkey focusing on deep learning applications in robotic manipulation. Master perception, grasp planning, and control through the use of neural networks and ROS 2. Engage in hands-on simulation exercises that prepare you to effectively deploy intelligent, adaptable grasping solutions on real robotic arms.