Deploying AI on Microcontrollers with TinyML - Plan Szkolenia

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

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

• Explore advanced techniques in Edge AI model development and optimization.
• Implement cutting-edge strategies for deploying AI models on edge devices.
• Utilize specialized tools and frameworks for advanced Edge AI applications.
• Optimize performance and efficiency of Edge AI solutions.
• Explore 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 Polsce (online or onsite) is aimed at intermediate-level developers, data scientists, and tech enthusiasts who wish to gain practical skills in deploying AI models on edge devices for various applications.

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

• Understand 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, live training in Polsce (online or onsite) is aimed at intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who wish to leverage Edge AI for innovative autonomous system solutions.

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

• Understand the role and benefits of Edge AI in autonomous systems.
• Develop and deploy AI models for real-time processing on edge devices.
• Implement Edge AI solutions in autonomous vehicles, drones, and robotics.
• Design and optimize control systems using Edge AI.
• Address ethical and regulatory considerations in autonomous AI applications.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI from concept to practical implementation, including setup and deployment.

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

• Understand the fundamental concepts of Edge AI.
• Set up and configure Edge AI environments.
• Develop, train, and optimize Edge AI models.
• Deploy and manage Edge AI applications.
• Integrate Edge AI with existing systems and workflows.
• Address ethical considerations and best practices in Edge AI implementation.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for innovative healthcare solutions.

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

• Understand the role and benefits of Edge AI in healthcare.
• Develop and deploy AI models on edge devices for healthcare applications.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems using Edge AI.
• Address ethical and regulatory considerations in healthcare AI applications.

To prowadzone przez instruktora szkolenie na żywo w Polsce (na miejscu lub zdalnie) jest przeznaczone dla inżynierów przemysłowych średniego szczebla, specjalistów ds. produkcji i programistów AI, którzy chcą wdrożyć rozwiązania Edge AI w automatyce przemysłowej.

Pod koniec tego szkolenia uczestnicy będą mogli

• Zrozumieć rolę Edge AI w automatyce przemysłowej.
• Wdrożyć rozwiązania konserwacji predykcyjnej przy użyciu Edge AI.
• Zastosować techniki AI do kontroli jakości w procesach produkcyjnych.
• Optymalizować procesy przemysłowe przy użyciu Edge AI.
• Wdrażać i zarządzać rozwiązaniami Edge AI w środowiskach przemysłowych.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

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

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level urban planners, civil engineers, and smart city project managers who wish to leverage Edge AI for smart city initiatives.

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

• Understand the role of Edge AI in smart city infrastructures.
• Implement Edge AI solutions for traffic management and surveillance.
• Optimize urban resources using Edge AI technologies.
• Integrate Edge AI with existing smart city systems.
• Address ethical and regulatory considerations in smart city deployments.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level developers, data scientists, and AI practitioners who wish to leverage TensorFlow Lite for Edge AI applications.

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

• Understand the fundamentals of TensorFlow Lite and its role in Edge AI.
• Develop and optimize AI models using TensorFlow Lite.
• Deploy TensorFlow Lite models on various edge devices.
• Utilize tools and techniques for model conversion and optimization.
• Implement practical Edge AI applications using TensorFlow Lite.

This instructor-led, live training in Polsce (online or onsite) is aimed at beginner-level developers and IT professionals who wish to understand the fundamentals of Edge AI and its introductory applications.

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

• Understand the basic concepts and architecture of Edge AI.
• Set up and configure Edge AI environments.
• Develop and deploy simple Edge AI applications.
• Identify and understand the use cases and benefits of Edge AI.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level AI developers, machine learning engineers, and system architects who wish to optimize AI models for edge deployment.

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

• Understand the challenges and requirements of deploying AI models on edge devices.
• Apply model compression techniques to reduce the size and complexity of AI models.
• Utilize quantization methods to enhance model efficiency on edge hardware.
• Implement pruning and other optimization techniques to improve model performance.
• Deploy optimized AI models on various edge devices.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level cybersecurity professionals, system administrators, and AI ethics researchers who wish to secure and ethically deploy Edge AI solutions.

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

• Understand the security and privacy challenges in Edge AI.
• Implement best practices for securing edge devices and data.
• Develop strategies to mitigate security risks in Edge AI deployments.
• Address ethical considerations and ensure compliance with regulations.
• Conduct security assessments and audits for Edge AI applications.

To prowadzone przez instruktora szkolenie na żywo w Polsce (online lub na miejscu) jest przeznaczone dla początkujących inżynierów i naukowców zajmujących się danymi, którzy chcą zrozumieć podstawy TinyML, zbadać jego zastosowania i wdrożyć modele sztucznej inteligencji na mikrokontrolerach.

Pod koniec tego szkolenia uczestnicy będą mogli

• Zrozumieć podstawy TinyML i jego znaczenie.
• Wdrażać lekkie modele AI na mikrokontrolerach i urządzeniach brzegowych.
• Optymalizować i dostrajać modele uczenia maszynowego pod kątem niskiego zużycia energii.
• Zastosować TinyML w rzeczywistych aplikacjach, takich jak rozpoznawanie gestów, wykrywanie anomalii i przetwarzanie dźwięku.

This instructor-led, live training in Polsce (online or onsite) is aimed at intermediate-level embedded engineers, IoT developers, and AI researchers who wish to implement TinyML techniques for AI-powered applications on energy-efficient hardware.

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

• Understand the fundamentals of TinyML and edge AI.
• Deploy lightweight AI models on microcontrollers.
• Optimize AI inference for low-power consumption.
• Integrate TinyML with real-world IoT applications.

To prowadzone przez instruktora szkolenie na żywo w Polsce (na miejscu lub zdalnie) jest przeznaczone dla średnio zaawansowanych programistów IoT, inżynierów wbudowanych i praktyków AI, którzy chcą wdrożyć TinyML do konserwacji predykcyjnej, wykrywania anomalii i aplikacji inteligentnych czujników.

Pod koniec tego szkolenia uczestnicy będą mogli

• Zrozumieć podstawy TinyML i jego zastosowania w IoT.
• Skonfigurować środowisko programistyczne TinyML dla projektów IoT.
• Rozwijać i wdrażać modele ML na mikrokontrolerach o niskim poborze mocy.
• Wdrożenie konserwacji predykcyjnej i wykrywania anomalii przy użyciu TinyML.
• Optymalizacja modeli TinyML pod kątem efektywnego wykorzystania energii i pamięci.