TinyML: Running AI on Ultra-Low-Power Edge Devices Training Course

Aimed at intermediate-level telecom professionals, AI engineers, and IoT specialists, this instructor-led live training in Denmark (online or onsite) examines how 5G networks drive Edge AI applications.

By the end of the session, participants will be equipped to:

• Comprehend the basics of 5G technology and its role in Edge AI.
• Implement AI models optimized for low-latency tasks in 5G settings.
• Establish real-time decision-making frameworks utilizing Edge AI and 5G links.
• Enhance AI workload efficiency on edge devices.

This instructor-led, live training in Denmark (online or onsite) is designed for advanced-level AI practitioners, researchers, and developers looking to master the latest advancements in Edge AI, optimize their models for edge deployment, and explore specialized applications across various industries.

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

• Investigate advanced techniques in Edge AI model development and optimization.
• Implement state-of-the-art strategies for deploying AI models on edge devices.
• Utilize specialized tools and frameworks for advanced Edge AI applications.
• Optimize the performance and efficiency of Edge AI solutions.
• Discover innovative use cases and emerging trends in Edge AI.
• Address advanced ethical and security considerations in Edge AI deployments.

This instructor-led, live training in Denmark (online or on-site) is designed for intermediate-level developers, data scientists, and tech enthusiasts aiming to acquire practical skills in deploying AI models on edge devices for various applications.

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

• Grasp the principles of Edge AI and its benefits.
• Set up and configure the edge computing environment.
• Develop, train, and optimize AI models for edge deployment.
• Implement practical AI solutions on edge devices.
• Evaluate and improve the performance of edge-deployed models.
• Address ethical and security considerations in Edge AI applications.

This instructor-led training in Denmark empowers advanced professionals to design, optimize, and deploy full-scale TinyML pipelines. Participants will gain the ability to collect data, train low-power models, and validate real-world applications through practical lab work.

This live, instructor-led training available in Denmark (online or onsite) targets senior cybersecurity professionals, AI engineers, and IoT developers aiming to implement effective security measures and resilience strategies for Edge AI systems.

By the end of the session, participants will be able to:

• Assess security risks and vulnerabilities in Edge AI deployments.
• Utilize encryption and authentication techniques for data security.
• Design resilient Edge AI architectures resistant to cyber threats.
• Apply secure deployment strategies for AI models in edge settings.

This instructor-led live training, delivered in Denmark (online or onsite), is tailored for intermediate-level embedded systems engineers and AI developers aiming to implement machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

Upon completion, participants will be capable of:

• Grasping the core principles of TinyML and its advantages for edge AI applications.
• Configuring a development environment tailored for TinyML projects.
• Training, refining, and implementing AI models on low-power microcontrollers.
• Leveraging TensorFlow Lite and Edge Impulse to build practical TinyML solutions.
• Optimizing AI models to meet power efficiency and memory limitations.

This live, instructor-led course in Denmark prepares advanced professionals to optimize TinyML models for resource-limited embedded devices. Learners will apply quantization and pruning, build low-latency inference pipelines, and evaluate performance against memory and energy constraints.

This instructor-led training in Denmark enables advanced professionals to safeguard TinyML pipelines on edge devices. You will learn to implement privacy-preserving techniques, harden models against adversarial threats, and apply best practices for secure data handling in constrained environments.

Aimed at novice engineers and data scientists, this instructor-led live session in Denmark (either online or on-site) provides a comprehensive look at TinyML basics, its various applications, and the deployment of AI models on microcontrollers.

By the time the session concludes, participants will be capable of:

• Understanding the core tenets of TinyML and its relevance.
• Executing lightweight AI models on microcontrollers and edge devices.
• Refining and tuning machine learning models to ensure low power consumption.
• Applying TinyML to real-world scenarios including gesture detection, anomaly identification, and audio analysis.

This live, instructor-led training in Denmark guides advanced professionals in integrating TinyML into autonomous robotics. Attendees will learn to design optimized models, construct on-device perception pipelines, and implement lightweight AI on embedded hardware to achieve real-time autonomy.

This live, instructor-led training in Denmark explores the implementation of TinyML for healthcare monitoring and diagnostics. Learners will master the design of models for real-time health data, optimization for low-power wearables, and strategies for ensuring clinical reliability. The curriculum includes hands-on laboratory exercises.

This live, instructor-guided training in Denmark (online or onsite) is crafted for intermediate IoT developers, embedded engineers, and AI practitioners seeking to implement TinyML for predictive maintenance, anomaly detection, and smart sensor functionalities.

By the end of the session, participants will be able to:

• Understand the basics of TinyML and its IoT applications.
• Establish a TinyML development setup for IoT projects.
• Create and implement ML models on low-power microcontrollers.
• Use TinyML to build predictive maintenance and anomaly detection features.
• Refine TinyML models for optimal power and memory performance.

This 21-hour instructor-led course in Denmark enables intermediate professionals to implement TinyML for smart agriculture. Participants will learn to create lightweight models, integrate edge AI with IoT systems, and optimize solutions for precision irrigation and pest detection within a hands-on lab environment.