NobleProg delivers high-quality AI for Robotics training courses in Berlin, the dynamic heart of Germany's tech and innovation sector. Participants benefit from expert-led instruction tailored to the professional needs of the capital's diverse industry landscape. Join our Berlin-based programs to enhance your skills with hands-on learning experiences in a world-class urban environment.
AI for Robotics marks the convergence of intelligence and motion — the space where algorithms process, sensors interpret, and machines operate with intent. It is the cutting-edge domain where data translates into dexterity, driving the evolution of autonomous systems, industrial robotics, and intelligent machinery.
In these instructor-led live training sessions, participants discover how artificial intelligence evolves robotics into adaptive, learning-capable systems. Through practical exercises, they delve into perception models, motion planning, reinforcement learning, and AI-driven control frameworks that enhance machine responsiveness to approximate human-like agility.
For those joining online, the environment replicates the dynamic pace of physical laboratories — with step-by-step guidance through live demos and collaborative coding via an interactive remote desktop. Each session evolves into a collective inquiry into logic and movement, rather than a passive lecture.
For teams that prefer to develop and verify in a shared physical space, onsite live training in Berlin — conducted at client locations or NobleProg corporate training centers — converts learning into active experimentation. In this practical setting, robotics, code, and creativity intersect, allowing theoretical concepts to take tangible form.
Often referred to as Robotics AI or Intelligent Robotics, our training supports professionals in integrating software with mechanical systems — constructing architectures that sense, determine, and execute actions with growing autonomy and accuracy.
Our training facilities are located at Brückenstr. 4 in Berlin. Located on the fourth floor of a well-kept office building, our premises offer enough space for successful training courses in the heart of Berlin, within walking distance of the Jannowitzbrücke station.
Directions
The NobleProg training facilities are located in the heart of Berlin's Mitte district, just one underground station from Alexanderplatz, one of the centres of this vibrant city. By public transport you can reach us either by underground line U8 to Jannowitzbrücke station, followed by about 100 meters on foot.
Parking
Cars can be parked in the area along Brückenstr. and the nearby side streets, even if you may have to search for a moment. There is no charge for parking.
Local Amenities
Around the Rosenthaler Platz there are numerous small restaurants and shops where you can eat well and cheaply. There are also some hotels close by if you need accommodation for the training.
Our training facilities are located at Dianastrasse 46 in Potsdam-Babelsberg.
Our spacious training rooms are located directly opposite the Filmstudios Babelsberg and offer optimal training conditions for your needs.
Arrival
The NobleProg training facilities are conveniently located near the Medienstadt Babelsberg railway station,
and the A115 motorway is also easily accessible.
Parking
Parking is available in the surrounding streets around our training rooms.
Local Services
Potsdam offers numerous hotels and restaurants and is easily accessible thanks to its well-developed public transport system.
This practical, instructor-led training in Berlin focuses on rapid robotics prototyping leveraging ROS 2 and Docker. Learners will acquire hands-on expertise in efficiently building, testing, and deploying modular robotic systems, with a specific emphasis on containerization, simulation, and version control to support scalable development.
This practical HRI course in Berlin 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 improve both usability and safety.
This hands-on training in Berlin addresses ROS-PLC integration and digital twins within industrial automation. Participants will learn to synchronize robotic systems with PLCs, develop digital replicas for simulation, and optimize production workflows through real-time data exchange and advanced monitoring techniques.
Advanced training in Berlin focusing on deep learning for robotic manipulation. Acquire skills in perception, grasp planning, and control utilizing neural networks and ROS 2. Simulation-based hands-on exercises prepare you to effectively deploy intelligent, adaptive grasping solutions on physical robotic arms.
An advanced course in Berlin that focuses on the design and coordination of multi-robot systems. Participants will master the modeling of swarm intelligence, the implementation of distributed decision-making, and the optimization of inter-agent collaboration through hands-on simulation in ROS 2 and Gazebo, preparing them for real-world applications.
This instructor-led, live training in Berlin guides advanced professionals in integrating TinyML into autonomous robotics. Participants will design optimized models, implement on-device perception pipelines, and deploy lightweight AI on embedded hardware to enable real-time autonomy.
This 21-hour instructor-led training in Berlin focuses on safety cases, verification, and explainable AI in robotics. Participants will learn to apply hazard analysis, ethical governance, and compliance standards to ensure transparent and trustworthy robotic decision-making in real-world deployments.
This live training in Berlin guides intermediate engineers through the deployment of TinyML models for robotics. Participants will learn to optimize inference for speed and energy efficiency, integrate AI into control systems, and construct autonomous, low-latency robotic solutions directly on embedded hardware.
This live, instructor-led training on Berlin is accessible via online or onsite formats and is designed for intermediate-level learners seeking to investigate the impact of collaborative robots (cobots) and other human-centric AI frameworks in today’s workplaces.
By the conclusion of this program, participants will be positioned to:
Comprehend the core tenets of Human-Centric Physical AI and its real-world utility.
Investigate how collaborative robots drive productivity gains in professional settings.
Detect and mitigate issues arising from human-machine interactions.
Structure workflows that enhance cooperation between human teams and AI-powered systems.
Foster an environment of creative innovation and agile adaptation in organizations using AI.
This instructor-led live training in Berlin explores the principles of reinforcement learning and advanced deep RL methods such as PPO and DDPG. Participants will apply algorithms using Python and PyTorch, integrate them with ROS 2 and OpenAI Gym, and train autonomous robots to address complex tasks.
This instructor-led training in Berlin focuses on computer vision for robotics, utilizing OpenCV and deep learning. Participants will acquire the skills to implement perception pipelines, integrate detection models, and deploy systems on embedded platforms to achieve autonomous control.
This instructor-led, live training in Berlin (online or onsite) is tailored for advanced robotics engineers and AI researchers. It focuses on utilizing Multimodal AI to integrate various sensory data streams, enabling the creation of highly autonomous and efficient robots that can perceive and interact with their surroundings through sight, sound, and touch.
By the end of this program, 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.
In Berlin, this live training empowers advanced engineers with AI capabilities for robotic perception, planning, and control. Participants will leverage sensor fusion, craft motion algorithms, and implement learning-based strategies to effectively integrate intelligent systems into smart manufacturing workflows.
This instructor-led live training in Berlin empowers intermediate robotics engineers with practical expertise in autonomous navigation and SLAM utilizing ROS 2. Participants will learn to integrate LiDAR sensors, apply mapping algorithms, conduct simulations in Gazebo, and deploy functional navigation stacks on real-world physical robots.
This live, instructor-led training in Berlin, delivered either online or on-site, is designed for intermediate-level participants looking to refine their skills in designing, programming, and deploying intelligent robotic systems for automation and broader applications.
By the end of the training, participants will be able to:
Grasp the principles of Physical AI and its relevance in robotics and automation.
Design and program intelligent robotic systems suited for dynamic environments.
Implement AI models that drive autonomous decision-making in robotic systems.
Apply simulation tools for effective robotic testing and optimization.
Navigate complex challenges such as sensor fusion, real-time data processing, and energy efficiency.
This instructor-led live training on Berlin delves into the core concepts and hands-on fundamentals of AI for Robotics. It helps participants develop practical skills that directly apply to real-world work environments and modern business needs, utilizing ROS 2, TensorFlow, and OpenCV.
This instructor-led live training in Berlin guides developers through the process of building and deploying bots from the ground up. Participants will investigate essential frameworks, design conversational logic, and develop sample chatbots for both Facebook Messenger and the Microsoft Bot Framework.
This instructor-led, live training in Berlin (available online or onsite) is tailored for engineers looking to explore the application of artificial intelligence within mechatronic systems.
By the conclusion of this training, participants will have the ability to:
Develop a broad understanding of artificial intelligence, machine learning, and computational intelligence.
Comprehend the underlying concepts of neural networks and distinct learning methods.
Effectively select artificial intelligence approaches for solving real-life problems.
Deploy AI applications in the field of mechatronic engineering.
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Testimonials (2)
Supply of the materials (virtual machine) to get straight into the excersises, and the explanation of the Ros2 core. Why things work a certain way.
Arjan Bakema
Course - Autonomous Navigation & SLAM with ROS 2
its knowledge and utilization of AI for Robotics in the Future.
Ryle - PHILIPPINE MILITARY ACADEMY
Course - Artificial Intelligence (AI) for Robotics
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