AI for Robotics Training in Nepal

This instructor-led, practical training on Nepal focuses on rapid prototyping for robotics via ROS 2 and Docker. Participants gain proficiency in efficiently building, testing, and deploying modular robotic systems, developing hands-on expertise in containerization, simulation, and version control to support scalable development efforts.

This hands-on HRI course in Nepal focuses on voice, gesture, and collaborative control. It guides you through 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 Nepal focuses on ROS-PLC integration and digital twins for industrial automation. Participants will learn to synchronize robotic systems with PLCs, create digital replicas for simulation purposes, and optimize production workflows through real-time data exchange and advanced monitoring techniques.

An advanced training in Nepal focused on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control utilizing neural networks and ROS 2. Practical simulation exercises equip you to deploy intelligent, adaptable grasping solutions on real robotic arms with efficacy.

Advanced training in Nepal focused on the design and coordination of multi-robot systems. Participants will learn to model swarm intelligence, deploy distributed decision-making, and optimize inter-agent collaboration through hands-on simulation using ROS 2 and Gazebo, preparing them for real-world applications.

This instructor-led, live training in Nepal empowers advanced professionals 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 Nepal covers safety cases, verification, and explainable AI for robotics. Learn to apply hazard analysis, ethical governance, and compliance standards to ensure transparent, trustworthy robotic decision-making in real-world deployments.

This live training in Nepal empowers intermediate engineers to deploy TinyML models effectively for robotics. Participants will learn to optimize inference for speed and energy efficiency, integrate AI into control systems, and develop autonomous, low-latency robotic solutions directly on embedded hardware.

This instructor-led, live training in Nepal (online or onsite) is tailored for intermediate-level participants interested in exploring 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.

Offered as an instructor-led live training in Nepal, this program delves into reinforcement learning fundamentals and deep RL strategies such as PPO and DDPG. Learners will build algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to tackle complex tasks effectively.

This instructor-led training in Nepal focuses on applying computer vision to robotics using OpenCV and deep learning. Participants will gain the skills to implement perception pipelines, integrate detection models, and deploy systems on embedded platforms for autonomous control.

This instructor-led, live training in Nepal (online or onsite) targets advanced robotics engineers and AI researchers seeking to apply Multimodal AI. The objective is to merge various sensory data streams to construct robots that are more autonomous and efficient, possessing the ability to see, hear, and touch.

By the conclusion 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 Nepal equips intermediate robotics engineers with hands-on skills in autonomous navigation and SLAM using ROS 2. Learn to integrate LiDAR sensors, implement mapping algorithms, simulate in Gazebo, and deploy real-world navigation stacks on physical robots.

This live, instructor-led session in Nepal (delivered online or onsite) targets intermediate-level participants aiming to refine their capabilities in designing, programming, and implementing intelligent robotic systems for automation and beyond.

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

• Comprehend the foundational principles of Physical AI and its practical uses in robotics and automation.
• Architect and program intelligent robotic systems suited for dynamic settings.
• Integrate AI models to facilitate autonomous decision-making in robots.
• Employ simulation tools for effective robotic testing and performance tuning.
• Manage critical technical aspects such as sensor fusion, real-time processing, and energy management.

This instructor-led, live training in Nepal (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 a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Grasp the concepts of neural networks and various learning methodologies.
• Select appropriate artificial intelligence approaches for addressing real-world problems.
• Implement AI applications within the field of mechatronic engineering.