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

This instructor-led, live training in Taiwan (online or onsite) targets intermediate-level telecom professionals, AI engineers, and IoT specialists interested in exploring how 5G networks accelerate Edge AI applications.

Upon completing this training, participants will be able to:

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

6G and the Intelligent Edge is a forward-looking course that explores the integration of 6G wireless technologies with edge computing, IoT ecosystems, and AI-driven data processing to support intelligent, low-latency, and adaptive infrastructures.

This instructor-led, live training (online or onsite) is aimed at intermediate-level IT architects who wish to understand and design next-generation distributed architectures leveraging the synergy of 6G connectivity and intelligent edge systems.

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

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

Format of the Course

• Interactive lectures and discussions.
• Case studies and applied architecture design exercises.
• Hands-on simulation with 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 Taiwan (online or onsite) targets 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.

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

• Investigate advanced techniques in Edge AI model development and optimization.
• Execute state-of-the-art 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.
• Address advanced ethical and security considerations in Edge AI deployments.

This instructor-led, live training in Taiwan (available online or onsite) is tailored for intermediate-level developers, data scientists, and tech enthusiasts seeking 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.

AI-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. This approach shifts organizations from reactive maintenance models to proactive strategies, resulting in improved uptime, reduced costs, and extended asset lifespan.

This instructor-led training, available online or onsite, is designed for intermediate-level professionals seeking to implement AI-driven predictive maintenance solutions within industrial environments.

Upon completing this training, participants will be able to:

• Distinguish between predictive maintenance and reactive or preventive maintenance strategies.
• Gather and organize machine data for AI-driven analysis.
• Utilize machine learning models to identify anomalies and forecast equipment failures.
• Deploy end-to-end workflows that transform raw sensor data into actionable insights.

Course Format

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

Customization Options

• To request tailored training for this course, please contact us to make arrangements.

Leveraging AI for Process Optimization involves utilizing machine learning and data analytics to boost efficiency, enhance quality, and increase throughput in manufacturing settings.

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

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

• Grasp AI concepts pertinent to manufacturing optimization.
• Gather and prepare production data for analysis.
• Deploy machine learning models to pinpoint bottlenecks and forecast failures.
• Visualize and interpret results to facilitate data-driven decision-making.

Course Format

• Interactive lectures and discussions.
• Extensive exercises and practice sessions.
• Practical implementation within a live-lab environment.

Course Customization Options

• To request customized training for this course, please reach out to us to make arrangements.

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

This instructor-led live training (available online or onsite) targets beginner to intermediate quality professionals who aim to leverage AI tools to automate inspections and enhance product quality in manufacturing environments.

Upon completion 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.

Leveraging AI in supply chain and manufacturing logistics involves applying predictive analytics, machine learning, and automation to enhance inventory management, optimize routing, and improve demand forecasting.

This instructor-led live training, available online or onsite, is designed for intermediate-level supply chain professionals seeking to utilize AI-driven tools to boost logistics performance, achieve accurate demand forecasting, and automate warehouse and transportation operations.

Upon completing this training, participants will be able to:

• Gain insights into how AI is utilized across logistics and supply chain activities.
• Apply machine learning models to forecast demand and manage inventory.
• Analyze and optimize transport routes using AI-based techniques.
• Automate decision-making processes in warehouses and fulfillment operations.

Course Format

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

Course Customization Options

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

The application of artificial intelligence in smart factories involves automating, monitoring, and optimizing 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:

• Comprehend the fundamental 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.

Course Format

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

Course Customization Options

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

This AI Use Case Implementation workshop adopts a project-driven, hands-on methodology to apply machine learning, computer vision, and data analytics for resolving real-world industrial challenges, utilizing actual or simulated datasets.

Delivered as an instructor-led, live training session (available online or onsite), this program targets intermediate-level cross-functional teams aiming to collaboratively execute AI use cases 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 control, or maintenance.
• Collaborate across different roles to develop machine learning solutions.
• Manage, clean, and analyze diverse industrial datasets.
• Present a functional prototype of an AI-enabled solution based on a selected use case.

Course Format

• Interactive lectures and discussions.
• Group-based exercises and project work.
• Hands-on implementation within a live laboratory environment.

Course Customization Options

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

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

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

• Understand security risks and vulnerabilities in Edge AI deployments.
• Implement encryption and authentication techniques for data protection.
• Design resilient Edge AI architectures that can withstand cyber threats.
• Apply secure AI model deployment strategies in edge environments.

Cambricon MLUs (Machine Learning Units) are specialized AI chips optimized for inference and training in edge and datacenter scenarios.

This instructor-led, live training (online or onsite) is aimed at intermediate-level developers who wish to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

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

• Set up and configure the BANGPy and Neuware development environments.
• Develop and optimize Python- and C++-based models for Cambricon MLUs.
• Deploy models to edge and data center devices running Neuware runtime.
• Integrate ML workflows with MLU-specific acceleration features.

Format of the Course

• Interactive lecture and discussion.
• Hands-on use of BANGPy and Neuware for development and deployment.
• Guided exercises focused on optimization, integration, and testing.

Course Customization Options

• To request a customized training for this course based on your Cambricon device model or use case, please contact us to arrange.

Digital Twins serve as virtual replicas of physical systems, augmented by real-time data and AI-driven intelligence.

This instructor-led live training, available either online or onsite, targets intermediate-level professionals eager to construct, deploy, and optimize digital twin models leveraging real-time data and AI insights.

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

• Comprehending the architecture and components of digital twins.
• Employing simulation tools to model intricate systems and environments.
• Integrating real-time data streams into virtual models.
• Applying AI methodologies for predictive behavior analysis and anomaly detection.

Course Format

• Interactive lectures and discussions.
• Numerous exercises and practical applications.
• Hands-on implementation within a live-lab setting.

Course Customization Options

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

AI-driven industrial computer vision is revolutionizing the way manufacturers and QA teams identify surface defects, verify part compliance, and automate visual inspection workflows.

This instructor-led, live training (available online or onsite) targets intermediate to advanced QA teams, automation engineers, and developers aiming to design and deploy computer vision systems for defect detection and inspection using AI methodologies.

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

• Gaining a comprehensive understanding of industrial vision system architecture and components.
• Developing AI models for visual defect detection utilizing deep learning techniques.
• Integrating real-time inspection pipelines with industrial cameras and devices.
• 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-lab environment.

Course Customization Options

• For customized training requests for this course, please contact us to arrange.

Smart robotics integrates artificial intelligence into robotic systems to enhance perception, decision-making, and autonomous control.

This instructor-led live training (available online or onsite) is designed for advanced-level robotics engineers, systems integrators, and automation leads who want to implement AI-driven perception, planning, and control in smart manufacturing settings.

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.
• Extensive 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.