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

This instructor-led, live training in Malaysia (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists keen to explore 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 tailored for low-latency applications within 5G environments.
• Implement real-time decision-making systems leveraging Edge AI and 5G connectivity.
• Optimise AI workloads for efficient performance on edge devices.

This forward-looking course examines how 6G wireless technologies integrate with edge computing, IoT ecosystems, and AI-driven data processing to build intelligent, low-latency, and adaptive infrastructures.

Designed for intermediate-level IT architects, this instructor-led live training (available online or onsite) helps participants 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 business and operational models enabled by the convergence of 6G and edge technologies.

Course Format

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

Customization Options

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

This instructor-led, live training in Malaysia (online or on-site) 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 Malaysia (online or onsite) is designed for intermediate-level developers, data scientists, and tech enthusiasts looking to gain 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. It shifts the paradigm from reactive maintenance to proactive strategies, resulting in improved uptime, reduced costs, and extended asset life.

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

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

• Distinguish predictive maintenance from reactive and preventive maintenance strategies.
• Gather and structure machine data for AI analysis.
• Utilize machine learning models to identify anomalies and forecast failures.
• Execute end-to-end workflows that transform sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Practical exercises and case study analyses.
• Live demonstrations and hands-on data workflow practices.

Customization Options

• For tailored training requests, please get in touch with us to arrange your specific requirements.

AI for Process Optimization involves leveraging machine learning and data analytics to boost efficiency, quality, and throughput within manufacturing operations.

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

Upon completing this training, participants will be able to:

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

Course Format

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

Course Customization Options

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

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

This instructor-led live training, available either online or onsite, is designed for quality professionals at beginner to intermediate levels who aim to utilize 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.
• Collect and label image or sensor data from production lines.
• Utilize machine learning and computer vision for defect detection.
• Develop basic AI models for anomaly detection and yield forecasting.

Format of the Course

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

Course Customization Options

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

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

This instructor-led live training, available online or onsite, is designed for intermediate-level supply chain professionals looking to leverage AI-driven tools to enhance logistics performance, improve demand forecast 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.

AI in Smart Factories involves applying artificial intelligence to automate, monitor, and optimise industrial operations in real time.

This instructor-led live training (available online or onsite) is designed for beginner-level decision-makers and technical leads who want a strategic and practical introduction to leveraging AI 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 optimisation.
• 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.

Implementing AI Use Cases utilizes a hands-on, project-focused methodology to apply machine learning, computer vision, and data analytics to address real-world industrial challenges by leveraging actual or simulated datasets.

This instructor-led, live training (available online or onsite) is designed for intermediate-level cross-functional teams seeking to collaboratively implement AI initiatives aligned with their operational objectives and build experience with industrial data pipelines.

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

• Identifying and defining practical AI scenarios within operations, quality, or maintenance functions.
• Collaborating across various roles to develop machine learning solutions.
• Managing, cleaning, and analyzing diverse industrial datasets.
• Demonstrating a functional prototype of an AI-enabled solution derived from a chosen scenario.

Course Format

• Interactive lectures and discussions.
• Group-based exercises and project work.
• Practical implementation within a live-lab environment.

Customization Options

• To arrange customized training for this course, please contact us to discuss your requirements.

This instructor-led, live training in Malaysia (online or onsite) is aimed at 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 artificial intelligence chips designed to optimize inference and training tasks for both edge computing and data center environments.

This instructor-led live training, available online or onsite, 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 capable of:

• Setting up and configuring development environments for BANGPy and Neuware.
• Creating and optimizing Python and C++ based models for Cambricon MLUs.
• Deploying models to edge and data center devices operating on the Neuware runtime.
• Integrating machine learning workflows with acceleration features specific to MLU.

Course Format

• Interactive lectures and discussions.
• Practical application of BANGPy and Neuware for development and deployment.
• Guided exercises focusing on optimization, integration, and testing.

Customization Options

• For a customized training session tailored to your specific Cambricon device model or use case, please contact us to make arrangements.

Digital Twins serve as virtual mirrors of physical systems, augmented by real-time data feeds and AI-powered analytics.

This instructor-led training, available online or onsite, is designed for intermediate-level professionals seeking to construct, deploy, and refine digital twin models leveraging real-time information and AI-driven insights.

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

• Grasp the architecture and key components of digital twins.
• Utilize simulation tools to represent complex systems and environments.
• Incorporate real-time data streams into virtual models.
• Deploy AI methodologies for predictive analysis and anomaly identification.

Course Format

• Engaging lectures and interactive discussions.
• Extensive practical exercises and hands-on practice.
• Live-lab implementation sessions.

Customization Options

• For tailored training arrangements, please get in touch with us.

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

This instructor-led live training, available both online and onsite, is designed for intermediate to advanced quality assurance teams, automation engineers, and developers who want 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:

• Grasp the architecture and key components of industrial vision systems.
• Develop 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 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

• To arrange customized training for this course, please get in touch with us.

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

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

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

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

Format of the Course

• 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 contact us to arrange the details.