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

Denna instruktörsledda, liveutbildning i Sverige (online eller på plats) riktar sig till AI-utövare, forskare och utvecklare på avancerad nivå som vill behärska de senaste framstegen inom Edge AI, optimera sina AI-modeller för edge-distribution och utforska specialiserade applikationer inom olika branscher.

I slutet av denna utbildning kommer deltagarna att kunna:

• Utforska avancerade tekniker inom utveckling och optimering av AI-modeller för gränsenheter.
• Implementera banbrytande strategier för att distribuera AI-modeller på gränsenheter.
• Använd specialiserade verktyg och ramverk för avancerade Edge AI-applikationer.
• Optimera prestanda och effektivitet för Edge AI-lösningar.
• Utforska innovativa användningsfall och nya trender inom Edge AI.
• Hantera avancerade etiska överväganden och säkerhetsöverväganden i Edge AI-distributioner.

Denna instruktörsledda, liveutbildning i Sverige (online eller på plats) riktar sig till utvecklare på mellannivå, datavetare och teknikentusiaster som vill få praktiska färdigheter i att distribuera AI-modeller på edge-enheter för olika applikationer.

I slutet av denna utbildning kommer deltagarna att kunna:

• Förstå principerna för Edge AI och dess fördelar.
• Konfigurera databehandlingsmiljön på gränsenheter.
• Utveckla, träna och optimera AI-modeller för gränsdistribution.
• Implementera praktiska AI-lösningar på gränsenheter.
• Utvärdera och förbättra prestanda för gränsdistribuerade modeller.
• Ta itu med etiska överväganden och säkerhetsöverväganden i Edge AI-program.

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.

Denna instruktörsledda, liveutbildning i Sverige (online eller på plats) riktar sig till utvecklare och IT-proffs på mellannivå som vill få en omfattande förståelse för Edge AI från koncept till praktisk implementering, inklusive installation och distribution.

I slutet av denna utbildning kommer deltagarna att kunna:

• Förstå de grundläggande begreppen för Edge AI.
• Konfigurera Edge AI-miljöer.
• Utveckla, träna och optimera Edge AI-modeller.
• Distribuera och hantera Edge AI-program.
• Integrera Edge AI med befintliga system och arbetsflöden.
• Ta itu med etiska överväganden och bästa praxis vid implementering av AI på gränsenheter.

Denna instruktörsledda, liveutbildning i Sverige (online eller på plats) riktar sig till vårdpersonal på mellannivå, biomedicinska ingenjörer och AI-utvecklare som vill utnyttja Edge AI för innovativa hälso- och sjukvårdslösningar.

I slutet av denna utbildning kommer deltagarna att kunna:

• Förstå rollen och fördelarna med Edge AI inom hälso- och sjukvården.
• Utveckla och distribuera AI-modeller på gränsenheter för hälso- och sjukvårdsprogram.
• Implementera Edge AI-lösningar i bärbara enheter och diagnostikverktyg.
• Utforma och distribuera patientövervakningssystem med hjälp av Edge AI.
• Ta itu med etiska och regulatoriska överväganden i AI-tillämpningar för hälso- och sjukvård.

Denna instruktörsledda, liveutbildning i Sverige (online eller på plats) riktar sig till utvecklare på mellannivå, systemarkitekter och branschfolk som vill utnyttja Edge AI för att förbättra IoT-applikationer med intelligenta databehandlings- och analysfunktioner.

I slutet av denna utbildning kommer deltagarna att kunna:

• Förstå grunderna i Edge AI och dess tillämpning i IoT.
• Konfigurera Edge AI-miljöer för IoT-enheter.
• Utveckla och distribuera AI-modeller på gränsenheter för IoT-program.
• Implementera databehandling och beslutsfattande i realtid i IoT-system.
• Integrera Edge AI med olika IoT-protokoll och plattformar.
• Ta itu med etiska överväganden och metodtips i Edge AI för 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.

Denna instruktörsledda, liveutbildning i Sverige (online eller på plats) riktar sig till utvecklare och IT-proffs på nybörjarnivå som vill förstå grunderna i Edge AI och dess introduktionsapplikationer.

I slutet av denna utbildning kommer deltagarna att kunna:

• Förstå de grundläggande begreppen och arkitekturen för Edge AI.
• Konfigurera Edge AI-miljöer.
• Utveckla och distribuera enkla Edge AI-program.
• Identifiera och förstå användningsfallen och fördelarna med 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.