Edge AI for Manufacturing: Real-Time Intelligence at the Device Level Training Course

Това водено от инструктор обучение на живо в България (онлайн или на място) е насочено към AI практици, изследователи и разработчици на напреднало ниво, които желаят да овладеят най-новите постижения в Edge AI, да оптимизират своите AI модели за крайно внедряване и да изследват специализирани приложения в различни индустрии.

До края на това обучение участниците ще могат:

• Разгледайте усъвършенствани техники в разработването и оптимизирането на модели на Edge AI.
• Приложете авангардни стратегии за внедряване на AI модели на крайни устройства.
• Използвайте специализирани инструменти и рамки за усъвършенствани Edge AI приложения.
• Оптимизирайте производителността и ефективността на решенията Edge AI.
• Разгледайте иновативни случаи на употреба и нововъзникващи тенденции в Edge AI.
• Обърнете внимание на разширени етични съображения и съображения за сигурност при внедряването на Edge AI.

Това водено от инструктор обучение на живо в България (онлайн или на място) е насочено към разработчици на средно ниво, учени по данни и технически ентусиасти, които желаят да придобият практически умения за внедряване на AI модели на крайни устройства за различни приложения.

До края на това обучение участниците ще могат:

• Разберете принципите на Edge AI и неговите предимства.
• Настройте и конфигурирайте периферната изчислителна среда.
• Разработвайте, обучавайте и оптимизирайте AI модели за крайно внедряване.
• Внедрете практични AI решения на крайни устройства.
• Оценете и подобрете производителността на моделите, разгърнати на ръба.
• Обърнете внимание на етични съображения и съображения за сигурност в приложенията на Edge AI.

AI-powered predictive maintenance applies machine learning and data analytics to forecast equipment failures and optimize maintenance schedules. It transforms reactive maintenance models into proactive strategies, enabling better uptime, cost reduction, and asset longevity.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to implement AI-driven predictive maintenance solutions in industrial environments.

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

• Understand how predictive maintenance differs from reactive and preventive maintenance strategies.
• Collect and structure machine data for AI-powered analysis.
• Apply machine learning models to detect anomalies and predict failures.
• Implement end-to-end workflows from sensor data to actionable insights.

Format of the Course

• Interactive lecture and discussion.
• Hands-on exercises and case studies.
• Live demonstration and practical data workflows.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI for Process Optimization is the application of machine learning and data analytics to enhance efficiency, quality, and throughput in manufacturing operations.

This instructor-led, live training (online or onsite) is aimed at intermediate-level manufacturing professionals who wish to apply AI techniques to streamline operations, reduce downtime, and support continuous improvement initiatives.

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

• Understand AI concepts relevant to manufacturing optimization.
• Collect and prepare production data for analysis.
• Apply machine learning models to identify bottlenecks and predict failures.
• Visualize and interpret results to support data-driven decisions.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI for Quality Control is the use of computer vision and machine learning techniques to identify defects, anomalies, and deviations in production processes.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level quality professionals who wish to apply AI tools to automate inspections and improve product quality in manufacturing environments.

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

• Understand how AI is applied in industrial quality control.
• Collect and label image or sensor data from production lines.
• Use machine learning and computer vision to detect defects.
• Develop simple AI models for anomaly detection and yield forecasting.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI in Supply Chain and Manufacturing Logistics is the application of predictive analytics, machine learning, and automation to optimize inventory, routing, and demand forecasting.

This instructor-led, live training (online or onsite) is aimed at intermediate-level supply chain professionals who wish to apply AI-driven tools to enhance logistics performance, forecast demand accurately, and automate warehouse and transport operations.

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

• Understand how AI is applied across logistics and supply chain activities.
• Use machine learning models for demand forecasting and inventory control.
• Analyze routes and optimize transport using AI-based techniques.
• Automate decision-making in warehouses and fulfillment processes.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI in Smart Factories is the application of artificial intelligence to automate, monitor, and optimize industrial operations in real time.

This instructor-led, live training (online or onsite) is aimed at beginner-level decision-makers and technical leads who wish to gain a strategic and practical introduction to how AI can be leveraged in smart factory environments.

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

• Understand the core principles of AI and machine learning.
• Identify key AI use cases in manufacturing and automation.
• Explore how AI supports predictive maintenance, quality control, and process optimization.
• Evaluate the steps involved in launching AI-driven initiatives.

Format of the Course

• Interactive lecture and discussion.
• Real-world case studies and group exercises.
• Strategic frameworks and implementation guidance.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI Use Case Implementation is a hands-on, project-driven approach to applying machine learning, computer vision, and data analytics to solve real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (online or onsite) is aimed at intermediate-level cross-functional teams who wish to collaboratively implement AI use cases aligned with their operational goals and gain experience working with industrial data pipelines.

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

• Select and scope practical AI use cases from operations, quality, or maintenance.
• Work collaboratively across roles to develop machine learning solutions.
• Handle, clean, and analyze diverse industrial datasets.
• Present a working prototype of an AI-enabled solution based on a selected use case.

Format of the Course

• Interactive lecture and discussion.
• Group-based exercises and project work.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Digital Twins are virtual replicas of physical systems enhanced by real-time data and AI-driven intelligence.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to build, deploy, and optimize digital twin models using real-time data and AI-based insights.

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

• Understand the architecture and components of digital twins.
• Use simulation tools to model complex systems and environments.
• Integrate real-time data streams into virtual models.
• Apply AI techniques for predictive behavior and anomaly detection.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Това водено от инструктор обучение на живо в България (онлайн или на място) е насочено към разработчици на средно ниво и ИТ специалисти, които желаят да придобият цялостно разбиране за Edge AI от концепцията до практическото внедряване, включително настройка и внедряване.

До края на това обучение участниците ще могат:

• Разберете основните концепции на Edge AI.
• Настройте и конфигурирайте Edge AI среди.
• Разработвайте, обучавайте и оптимизирайте Edge AI модели.
• Внедрете и управлявайте Edge AI приложения.
• Интегрирайте Edge AI със съществуващи системи и работни процеси.
• Обърнете внимание на етичните съображения и най-добрите практики при внедряването на Edge AI.

Това водено от инструктор обучение на живо в България (онлайн или на място) е насочено към здравни специалисти на средно ниво, биомедицински инженери и разработчици на AI, които желаят да използват Edge AI за иновативни решения в здравеопазването.

До края на това обучение участниците ще могат:

• Разберете ролята и предимствата на Edge AI в здравеопазването.
• Разработвайте и внедрявайте AI модели на крайни устройства за приложения в здравеопазването.
• Внедряване на Edge AI решения в носими устройства и инструменти за диагностика.
• Проектирайте и внедрявайте системи за наблюдение на пациенти с помощта на Edge AI.
• Обърнете внимание на етични и регулаторни съображения в приложенията на AI в здравеопазването.

Това водено от инструктор обучение на живо в България (онлайн или на място) е насочено към разработчици на средно ниво, системни архитекти и професионалисти в индустрията, които желаят да използват Edge AI за подобряване на IoT приложения с интелигентна обработка на данни и възможности за анализ.

До края на това обучение участниците ще могат:

• Разберете основите на Edge AI и приложението му в IoT.
• Настройте и конфигурирайте Edge AI среди за IoT устройства.
• Разработвайте и внедрявайте AI модели на крайни устройства за IoT приложения.
• Внедрете обработка на данни в реално време и вземане на решения в IoT системи.
• Интегрирайте Edge AI с различни IoT протоколи и платформи.
• Обърнете внимание на етичните съображения и най-добрите практики в Edge AI за IoT.

Industrial computer vision with AI is transforming how manufacturers and QA teams detect surface defects, verify part conformity, and automate visual inspection processes.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level QA teams, automation engineers, and developers who wish to design and implement computer vision systems for defect detection and inspection using AI techniques.

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

• Understand the architecture and components of industrial vision systems.
• Build AI models for visual defect detection using deep learning.
• Integrate real-time inspection pipelines with industrial cameras and devices.
• Deploy and optimize AI-powered inspection systems for production environments.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Това водено от инструктор обучение на живо в България (онлайн или на място) е насочено към начинаещи разработчици и ИТ специалисти, които желаят да разберат основите на Edge AI и неговите уводни приложения.

До края на това обучение участниците ще могат:

• Разберете основните концепции и архитектура на Edge AI.
• Настройте и конфигурирайте Edge AI среди.
• Разработвайте и внедрявайте прости приложения Edge AI.
• Идентифицирайте и разберете случаите на употреба и предимствата на Edge AI.

Smart Robotics is the integration of artificial intelligence into robotic systems for improved perception, decision-making, and autonomous control.

This instructor-led, live training (online or onsite) is aimed at advanced-level robotics engineers, systems integrators, and automation leads who wish to implement AI-driven perception, planning, and control in smart manufacturing environments.

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

• Understand and apply AI techniques for robotic perception and sensor fusion.
• Develop motion planning algorithms for collaborative and industrial robots.
• Deploy learning-based control strategies for real-time decision making.
• Integrate intelligent robotic systems into smart factory workflows.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.