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

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

Upon completion of 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 to achieve efficient performance on edge devices.

"6G and the Intelligent Edge" is a forward-looking course that delves into 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:

• Grasp 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 Mexico (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 Mexico (online or onsite) is aimed at intermediate-level developers, data scientists, and tech enthusiasts who wish 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. This approach shifts maintenance strategies from reactive to proactive, resulting in improved operational uptime, reduced costs, and extended asset lifespans.

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

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

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

Course Format

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

Customization Options

• To request a customized version of this course, please contact us to arrange.

AI for Process Optimization involves applying machine learning and data analytics to improve efficiency, quality, and throughput in manufacturing operations.

This instructor-led, live training (online or onsite) is designed for intermediate-level manufacturing professionals who want 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 leverages computer vision and machine learning techniques to identify defects, anomalies, and deviations within production processes.

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

Upon completing this training, participants will be able to:

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

Format of the Course

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

Course Customization Options

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

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

This instructor-led live training, available online or onsite, targets intermediate-level supply chain professionals seeking to apply AI-driven tools to enhance logistics performance, improve demand forecasting accuracy, and automate warehouse and transport operations.

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

• Understand the application of AI across logistics and supply chain activities.
• Utilize machine learning models for demand forecasting and inventory control.
• Analyze routes and optimize transport using AI-based techniques.
• Automate decision-making processes in warehouses and fulfillment operations.

Course Format

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

Customization Options

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

Artificial intelligence in smart factories involves using AI to automate, monitor, and optimize industrial operations in real time.

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

Upon completing this training, participants will be able to:

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

The implementation of AI use cases utilizes a hands-on, project-oriented methodology to apply machine learning, computer vision, and data analytics for addressing real-world industrial challenges through actual or simulated datasets.

This instructor-led, live training (available online or onsite) targets intermediate-level cross-functional teams seeking to collaboratively deploy AI solutions that align with their operational objectives and build experience working with industrial data pipelines.

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

• Identifying and defining practical AI use cases within operations, quality, or maintenance functions.
• Collaborating across various roles to create machine learning solutions.
• Managing, cleaning, and analyzing a variety of industrial datasets.
• Delivering a functional prototype of an AI-driven solution based on a chosen use case.

Course Format

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

Customization Options for the Course

• For requests to customize this training, please contact us to arrange.

This instructor-led, live training in Mexico (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 AI processors optimized for inference and training in both edge computing and data center environments.

This instructor-led, live training (available online or onsite) is designed for intermediate developers seeking to build and deploy AI models using the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completion 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 the Neuware runtime.
• Integrate machine learning workflows with MLU-specific acceleration features.

Course Format

• Interactive lectures and discussions.
• Hands-on development and deployment using BANGPy and Neuware.
• Guided exercises focused on optimization, integration, and testing.

Customization Options

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

Digital Twins serve as virtual counterparts to physical systems, bolstered by live data feeds and artificial intelligence capabilities.

This guided, live training session (available online or in-person) targets intermediate professionals aiming to create, implement, and refine digital twin models leveraging real-time data and AI-derived insights.

Upon completing this training, participants will be equipped to:

• Grasp the structure and key elements of digital twins.
• Employ simulation software to model intricate systems and environments.
• Embed live data streams into virtual models.
• Utilize AI methods for forecasting behavior and identifying anomalies.

Course Format

• Engaging lectures and discussions.
• Abundant exercises and practical application.
• Practical implementation within a live laboratory setting.

Customization Options

• For tailored training on this topic, please reach out to us to coordinate.

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

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

Upon completing 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.

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

This instructor-led live training, available online or onsite, targets advanced robotics engineers, systems integrators, and automation leads looking to implement AI-driven perception, planning, and control within smart manufacturing settings.

Upon completing this training, participants will be equipped to:

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

Course Format

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

Course Customization Options

• For customized training requests, please contact us to arrange details.