Edge AI Training in Prague

This instructor-led, live training in Prague (online or onsite) is designed for advanced AI researchers, data scientists, and security specialists who wish to implement federated learning techniques to train AI models across multiple edge devices while preserving data privacy.

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

• Understand the principles and benefits of federated learning in Edge AI.
• Implement federated learning models using TensorFlow Federated and PyTorch.
• Optimize AI training across distributed edge devices.
• Address data privacy and security challenges in federated learning.
• Deploy and monitor federated learning systems in real-world applications.

This instructor-led, live training in Prague (online or onsite) is designed for agritech professionals, IoT specialists, and AI engineers at the beginner to intermediate level who want to develop and deploy Edge AI solutions for smart farming.

Upon completion of this training, participants will be able to:

• Grasp the role of Edge AI in precision agriculture.
• Implement AI-driven systems for monitoring crops and livestock.
• Develop solutions for automated irrigation and environmental sensing.
• Enhance agricultural efficiency through real-time Edge AI analytics.

This instructor-led, live training in Prague (online or onsite) is designed for advanced cybersecurity professionals, AI engineers, and IoT developers who want to implement robust security measures and resilience strategies for Edge AI systems.

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

• Grasp the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to safeguard data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Deploy AI models securely within edge environments.

This instructor-led live training in Prague (online or onsite) is designed for beginner to intermediate retail technologists, AI developers, and business analysts who want to apply Edge AI solutions for smart checkout systems, inventory management, and personalized customer engagement.

Upon completing this training, participants will be capable of:

• Understanding how Edge AI enhances retail operations and customer experience.
• Implementing AI-powered smart checkout and cashier-less payment systems.
• Optimizing inventory management with real-time tracking and analytics.
• Utilizing computer vision and AI for personalized in-store experiences.

This instructor-led, live training in Prague (online or onsite) is designed for intermediate-level professionals in telecommunications, AI engineering, and IoT who want to explore how 5G networks accelerate Edge AI applications.

Upon completing this training, participants will be capable of:

• Grasping the core principles of 5G technology and its influence on Edge AI.
• Deploying AI models specifically optimized for low-latency requirements within 5G infrastructures.
• Building real-time decision-making systems that leverage Edge AI and 5G connectivity.
• Optimizing AI workloads to ensure efficient operation on edge devices.

This instructor-led, live training conducted in Prague (online or onsite) is designed for intermediate-level embedded AI developers and edge computing specialists who aim to fine-tune and optimize lightweight AI models for deployment on resource-constrained devices.

Upon completing this training, participants will be capable of:

• Choosing and adapting pre-trained models appropriate for edge deployment.
• Utilizing quantization, pruning, and other compression methods to minimize model size and latency.
• Fine-tuning models via transfer learning to achieve performance tailored to specific tasks.
• Deploying optimized models onto actual edge hardware platforms.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level to advanced-level computer vision engineers, AI developers, and IoT professionals who wish to implement and optimize computer vision models for real-time processing on edge devices.

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

• Understand the fundamentals of Edge AI and its applications in computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Use frameworks like TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimize AI models for performance, power efficiency, and low-latency inference.

This instructor-led, live training in Prague (online or onsite) targets intermediate-level embedded engineers, IoT developers, and AI researchers seeking to implement TinyML techniques for AI-powered applications on energy-efficient hardware.

Upon completion of this training, participants will be able to:

• Grasp the core principles of TinyML and edge AI.
• Deploy lightweight AI models onto microcontrollers.
• Optimize AI inference to minimize power consumption.
• Integrate TinyML into practical IoT applications.

This instructor-led, live training in Prague (online or onsite) is intended for intermediate to advanced-level robotics engineers, AI developers, and automation specialists seeking to implement Edge AI for robotics applications.

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

• Comprehend the role of Edge AI in autonomous systems.
• Deploy AI models on edge devices for real-time robotic applications.
• Optimize AI performance to enable low-latency decision-making.
• Integrate computer vision and sensor fusion to enhance robotic autonomy.

This practical course in Prague guides you through the deployment of agentic AI on resource-constrained hardware. Participants learn to develop, refine, and manage lightweight agents for local reasoning using Python, TensorFlow Lite, and PyTorch Mobile, thereby boosting speed, privacy, and reliability.

This instructor-led, live training in Prague (online or onsite) is designed for advanced AI engineers, embedded developers, and hardware engineers who aim to deploy AI models on low-power devices while minimizing energy consumption.

Upon completion of this training, participants will be able to:

• Comprehend the challenges of running AI on energy-efficient devices.
• Optimize neural networks for low-power inference.
• Apply quantization, pruning, and model compression techniques.
• Deploy AI models on edge hardware with minimal power usage.

This instructor-led, live training in Prague (online or onsite) is designed for intermediate-level AI developers, embedded engineers, and robotics engineers who aim to optimize and deploy AI models on NVIDIA Jetson platforms for edge applications.

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

• Understand the fundamentals of edge AI and NVIDIA Jetson hardware.
• Optimize AI models for deployment on edge devices.
• Use TensorRT for accelerating deep learning inference.
• Deploy AI models using JetPack SDK and ONNX Runtime.

This instructor-led, live training in Prague (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 live, instructor-led training in Prague (online or onsite) is tailored for intermediate-level developers, data scientists, and tech enthusiasts seeking to master the practical skills required for deploying AI models on edge devices across diverse applications.

By the end of this program, participants will be capable of:

• Understanding the fundamentals and benefits of Edge AI.
• Configuring the necessary edge computing environment.
• Developing and optimizing AI models for edge deployment.
• Implementing functional AI solutions on edge hardware.
• Evaluating and refining the performance of edge-deployed models.
• Addressing ethical and security aspects in Edge AI contexts.

This instructor-led, live training in Prague (online or onsite) is aimed at intermediate-level finance professionals, fintech developers, and AI specialists who wish to implement Edge AI solutions in financial services.

Upon completing this training, participants will be able to:

• Grasp the role of Edge AI in financial services.
• Deploy fraud detection systems using Edge AI.
• Improve customer service via AI-driven solutions.
• Apply Edge AI for risk management and decision-making.
• Deploy and manage Edge AI solutions in financial environments.

This instructor-led live training in Prague (online or onsite) targets intermediate-level industrial engineers, manufacturing professionals, and AI developers aiming to implement Edge AI solutions in industrial automation.

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

• Understand the role of Edge AI in industrial automation.
• Implement predictive maintenance solutions using Edge AI.
• Apply AI techniques for quality control in manufacturing processes.
• Optimize industrial processes using Edge AI.
• Deploy and manage Edge AI solutions in industrial environments.

This instructor-led, live training in Prague (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 live, instructor-led training in Prague (online or onsite) targets intermediate-level urban planners, civil engineers, and smart city project managers aiming to leverage Edge AI for municipal initiatives.

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

• Understand the function 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 Prague (online or onsite) is designed for intermediate-level cybersecurity professionals, system administrators, and AI ethics researchers who wish to secure and ethically deploy Edge AI solutions.

Upon completing this training, participants will be able to:

• Comprehend the security and privacy challenges inherent in Edge AI.
• Apply best practices for protecting edge devices and data.
• Formulate strategies to reduce security risks during Edge AI deployment.
• Handle ethical considerations and ensure adherence to regulations.
• Perform security assessments and audits for Edge AI applications.

This instructor-led, live training in Prague (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 Prague (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.

This 21-hour training in Prague empowers IT architects to design next-generation distributed systems. It covers the integration of 6G, edge computing, and AI to build low-latency, scalable infrastructures. Participants will acquire the practical skills necessary to create secure, resilient, and intelligent edge architectures that meet future business demands.

This instructor-led, live training in Prague (online or onsite) targets advanced-level AI practitioners, researchers, and developers aiming to master recent advancements in Edge AI, optimize their AI models for edge deployment, and explore specialized applications across diverse industries.

Upon completion of this training, participants will be able to:

• Investigate advanced techniques for developing and optimizing Edge AI models.
• Apply modern strategies for deploying AI models on edge devices.
• Leverage specialized tools and frameworks for advanced Edge AI applications.
• Enhance the performance and efficiency of Edge AI solutions.
• Discover innovative use cases and emerging trends in Edge AI.
• Tackle advanced ethical and security challenges in Edge AI deployments.

This instructor-led, live training in Prague (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 Prague (online or onsite) targets intermediate-level IoT developers, embedded engineers, and AI practitioners aiming to implement TinyML for predictive maintenance, anomaly detection, and smart sensor applications.

Upon completion of this training, participants will be able to:

• Grasp the core concepts of TinyML and its role in IoT.
• Establish a TinyML development environment for IoT initiatives.
• Create and deploy machine learning models on low-power microcontrollers.
• Apply TinyML for predictive maintenance and anomaly detection.
• Optimize TinyML models to maximize power efficiency and minimize memory usage.

This instructor-led, live training in Prague (online or onsite) is designed for 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 Prague (online or onsite) is designed for intermediate-level embedded systems engineers and AI developers who want to deploy machine learning models on microcontrollers using TensorFlow Lite and Edge Impulse.

Upon completing this training, participants will be able to:

• Grasp the core concepts of TinyML and understand its advantages for edge AI applications.
• Establish a development environment suitable for TinyML projects.
• Train, optimize, and deploy AI models on low-power microcontrollers.
• Utilize TensorFlow Lite and Edge Impulse to build real-world TinyML solutions.
• Optimize AI models to meet power efficiency and memory limitations.

This instructor-led, live training in Prague (online or onsite) is designed for beginner-level developers and IT professionals who want to grasp the fundamentals of Edge AI and explore its initial applications.

Upon completion of this training, participants will be able to:

• Comprehend the core concepts and architecture of Edge AI.
• Set up and configure environments for Edge AI.
• Create and deploy basic Edge AI applications.
• Recognize and appreciate the use cases and advantages of Edge AI.