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

This instructor-led, live training in Italy (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists eager to explore how 5G networks enhance Edge AI applications.

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

• Grasp the fundamentals of 5G technology and its influence on Edge AI.
• Deploy AI models tailored for low-latency applications within 5G environments.
• Implement real-time decision-making systems leveraging Edge AI and 5G connectivity.
• Optimize AI workloads to ensure efficient performance on edge devices.

6G and the Intelligent Edge offers a forward-looking exploration into how 6G wireless technologies integrate with edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (available online or onsite) is designed for intermediate-level IT architects looking to understand and design next-generation distributed architectures by leveraging the synergy between 6G connectivity and intelligent edge systems.

After completing this course, participants will be able to:

• Grasp how 6G will transform edge computing and IoT architectures.
• Design distributed systems capable of ultra-low latency, high bandwidth, and autonomous operations.
• Integrate AI and data analytics at the edge to enable intelligent decision-making.
• Plan scalable, secure, and resilient infrastructures ready for 6G.
• Evaluate the business and operational models enabled by the convergence of 6G and edge technologies.

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation using optional edge or container tools.

Course Customization Options

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

This instructor-led, live training in Italy (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 Italy (online or onsite) is designed for intermediate developers, data scientists, and technology enthusiasts who want to gain practical skills in deploying AI models on edge devices for diverse applications.

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

• Grasp the core principles of Edge AI and its advantages.
• Configure and set up the edge computing environment.
• Develop, train, and optimize AI models specifically for edge deployment.
• Implement functional AI solutions on edge devices.
• Assess and enhance the performance of models deployed at the edge.
• Tackle ethical and security aspects related to Edge AI applications.

AI-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts maintenance strategies from reactive to proactive, enhancing uptime, reducing costs, and extending asset lifespan.

This instructor-led live training (available online or onsite) is designed for intermediate-level professionals seeking to implement AI-powered predictive maintenance solutions in industrial settings.

Upon completing this training, participants will be able to:

• Distinguish predictive maintenance from reactive and preventive strategies.
• Gather and organize machine data for AI analysis.
• Utilize machine learning models to identify anomalies and predict failures.
• Develop complete workflows from sensor data to actionable insights.

Training Format

• Interactive lectures and discussions.
• Practical exercises and case studies.
• Live demonstrations and hands-on data workflows.

Customization Options

• For customized training arrangements, please contact us.

AI-driven process optimization involves applying machine learning algorithms and data analytics to boost efficiency, improve quality, and increase throughput within manufacturing environments.

This instructor-led live training, available both online and onsite, is designed for intermediate-level manufacturing professionals eager to utilize AI techniques to streamline operations, minimize downtime, and foster continuous improvement.

Upon completion of this course, participants will be equipped to:

• Grasp the AI concepts essential for manufacturing optimization.
• Gather and ready production data for in-depth analysis.
• Deploy machine learning models to pinpoint bottlenecks and anticipate failures.
• Visualize and interpret outcomes to facilitate data-informed decision-making.

Course Format

• Engaging lectures paired with interactive discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation for real-world application.

Customization Options

• For personalized training needs regarding this course, please reach out to us to make arrangements.

AI-driven Quality Control leverages computer vision and machine learning methodologies to identify defects, anomalies, and deviations within production processes.

This instructor-led, live training session (available online or onsite) is designed for quality professionals at the beginner to intermediate level who aim to implement AI tools to automate inspections and enhance product quality in manufacturing settings.

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

• Grasp the application of AI in industrial quality control.
• Gather and annotate image or sensor data from production lines.
• Utilize machine learning and computer vision techniques to detect defects.
• Construct basic AI models for anomaly detection and yield forecasting.

Course Format

• Engaging lectures paired with interactive discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Customization Options

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

AI in Supply Chain and Manufacturing Logistics leverages predictive analytics, machine learning, and automation to optimize inventory levels, routing efficiency, and demand forecasting.

This instructor-led live training (available online or onsite) is designed for intermediate-level supply chain professionals looking to apply AI-driven tools to improve logistics performance, forecast demand with greater accuracy, 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.

Artificial Intelligence in Smart Factories involves applying AI technologies to automate, monitor, and optimize industrial operations in real time.

This instructor-led live training, available online or onsite, is designed for beginner-level decision-makers and technical leads seeking a strategic and practical introduction to leveraging AI within smart factory environments.

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

• Grasp the fundamental principles of AI and machine learning.
• Recognize key AI applications in manufacturing and automation.
• Explore how AI facilitates predictive maintenance, quality control, and process optimization.
• Assess the steps required to launch AI-driven initiatives.

Course Format

• Interactive lectures and discussions.
• Real-world case studies and collaborative exercises.
• Strategic frameworks and implementation guidance.

Customization Options

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

This workshop offers a hands-on, project-oriented methodology for applying machine learning, computer vision, and data analytics to address real-world industrial challenges, utilizing either live or simulated datasets.

Designed as an instructor-led live session (available online or on-site), this training targets intermediate-level cross-functional teams seeking to collaboratively implement AI initiatives aligned with their operational objectives while gaining practical experience with industrial data pipelines.

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

• Identify and define practical AI use cases within operations, quality assurance, or maintenance.
• Collaborate effectively across different roles to engineer machine learning solutions.
• Manage, clean, and analyze a variety of industrial datasets.
• Develop and present a functional AI-enabled prototype based on a chosen use case.

Course Format

• Interactive lectures and discussions.
• Collaborative exercises and group project work.
• Practical implementation within a live laboratory environment.

Customization Options

• To request a customized version of this course, please get in touch with us to arrange.

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

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

• Comprehend the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to protect data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Execute secure AI model deployment strategies within edge environments.

Cambricon MLUs (Machine Learning Units) are specialized artificial intelligence chips designed to optimize both inference and training processes for edge computing and data center environments.

This instructor-led live training, available either online or on-site, is designed for intermediate-level developers aiming to build and deploy AI models utilizing the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

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

• Establish and configure development environments for both BANGPy and Neuware.
• Create and optimize models based on Python and C++ specifically for Cambricon MLUs.
• Deploy models to edge devices and data centers operating on the Neuware runtime.
• Integrate machine learning workflows with acceleration features specific to MLUs.

Course Format

• Engaging lectures combined with interactive discussions.
• Practical, hands-on experience with BANGPy and Neuware for development and deployment.
• Guided exercises emphasizing optimization, integration, and testing.

Customization Options

• To arrange customized training tailored to your specific Cambricon device model or use case, please contact us.

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.

Artificial intelligence is revolutionizing industrial computer vision, enabling manufacturers and quality assurance teams to detect surface defects, verify part conformity, and automate visual inspection processes more effectively.

This instructor-led live training, available both online and onsite, is designed for QA teams, automation engineers, and developers at the intermediate to advanced level who aim to design and implement AI-driven computer vision systems for defect detection and inspection.

Upon completion of this training, participants will be capable of:

• Gaining a clear understanding of the architecture and key components of industrial vision systems.
• Developing AI models for visual defect detection using deep learning techniques.
• Integrating real-time inspection pipelines with industrial cameras and hardware.
• Deploying and optimizing AI-powered inspection systems within production environments.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation in a live laboratory environment.

Customization Options

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

Smart Robotics involves integrating artificial intelligence into robotic systems to enhance perception, decision-making capabilities, and autonomous control.

This instructor-led live training, available either online or on-site, is designed for advanced robotics engineers, systems integrators, and automation leaders who aim to implement AI-driven perception, planning, and control within smart manufacturing settings.

Upon completing this training, participants will be capable of:

• Understanding and applying AI techniques for robotic perception and sensor fusion.
• Developing motion planning algorithms for both collaborative and industrial robots.
• Deploying learning-based control strategies to facilitate real-time decision making.
• Integrating intelligent robotic systems into smart factory workflows.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request customized training for this course, please reach out to us to arrange the details.