NobleProg delivers high-quality TinyML 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.
Delivered either online or on-site, these instructor-led live TinyML courses focus on interactive, hands-on practical experience. The primary goal is to demonstrate how to leverage machine learning on ultra-low-power devices, thereby enabling the development of AI-driven applications within resource-constrained environments.
TinyML training is offered as either "online live training" or "onsite live training." Online live training (also referred to as "remote live training") is conducted via an interactive remote desktop. Onsite live training can be conducted locally at the customer’s premises in Berlin or within NobleProg’s corporate training centers in Berlin.
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 instructor-led, live training in Berlin (online or onsite) targets intermediate-level embedded engineers, IoT developers, and AI researchers looking to implement TinyML techniques for AI-driven applications on energy-efficient hardware.
By the conclusion of this session, participants will have the capability to:
Comprehend the fundamental aspects of TinyML and edge AI.
Implement lightweight AI models on microcontroller platforms.
Fine-tune AI inference for minimal power usage.
Embed TinyML capabilities into practical IoT applications.
This instructor-led training in Berlin helps beginners and intermediate learners build practical TinyML applications using Raspberry Pi and Arduino. It covers data collection, model optimization, and edge deployment, guiding you to create efficient, real-world embedded AI prototypes.
This instructor-led program in Berlin empowers advanced professionals to architect, optimize, and deploy robust TinyML pipelines. Through practical laboratory work, participants will master data collection, low-power model training, and the testing of real-world applications.
This instructor-led training in Berlin empowers advanced professionals to secure TinyML pipelines on edge devices. It guides you in implementing privacy-preserving strategies, fortifying models against adversarial attacks, and applying secure data handling practices in constrained environments.
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 course in Berlin enables intermediate professionals to implement TinyML for smart agriculture. Participants will learn to construct lightweight models, integrate edge AI with IoT, and optimize systems for precision irrigation and pest detection through hands-on lab activities.
This live, instructor-led training for Berlin focuses on the deployment of TinyML for healthcare monitoring and diagnostics. Learners will acquire the skills to design models for real-time health data, optimize for low-power wearables, and guarantee clinical reliability. The curriculum includes hands-on laboratory exercises.
This instructor-led, live training in Berlin empowers advanced practitioners to fine-tune TinyML models for embedded devices with limited resources. Participants will master quantization and pruning, build low-latency inference pipelines, and evaluate performance against memory and energy constraints.
This instructor-led, live training in Berlin (online or onsite) is aimed at intermediate-level IoT developers, embedded engineers, and AI practitioners who wish to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.
By the end of this training, participants will be able to:
Understand the fundamentals of TinyML and its applications in IoT.
Set up a TinyML development environment for IoT projects.
Develop and deploy ML models on low-power microcontrollers.
Implement predictive maintenance and anomaly detection using TinyML.
Optimize TinyML models for efficient power and memory usage.
This instructor-led, live training in Berlin (online or onsite) is tailored for intermediate-level embedded systems engineers and AI developers looking to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.
By the conclusion of this session, participants will be capable of:
Comprehending the essentials of TinyML and its value proposition for edge AI.
Establishing a dedicated development workspace for TinyML tasks.
Training, optimizing, and deploying AI models on energy-efficient microcontrollers.
Utilizing TensorFlow Lite and Edge Impulse to create real-world TinyML solutions.
Enhancing model performance regarding power consumption and memory footprint.
This live, instructor-led training in Berlin (delivered online or onsite) is tailored for junior engineers and data scientists seeking to master the basics of TinyML, examine its diverse applications, and implement AI models on microcontrollers.
Upon completion, participants will be equipped to:
Grasp the core concepts of TinyML and its broader impact.
Implement lightweight AI models on microcontrollers and edge hardware.
Refine and optimize machine learning models for low-energy operation.
Utilize TinyML in practical scenarios, including gesture identification, anomaly monitoring, and audio analysis.
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