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

This instructor-led, live training in Nigeria (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists eager to discover 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 to ensure 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 Nigeria (online or onsite) targets advanced-level AI practitioners, researchers, and developers seeking 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 Nigeria (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-powered predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and optimize maintenance schedules. It shifts organizations from reactive maintenance models to proactive strategies, resulting in improved uptime, reduced costs, and extended asset lifespan.

This instructor-led live 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 predictive maintenance from reactive and preventive maintenance strategies.
• Collect and structure machine data for AI-driven analysis.
• Apply machine learning models to detect anomalies and predict failures.
• Implement end-to-end workflows transforming sensor data into actionable insights.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises and case studies.
• Live demonstrations and practical data workflows.

Customization Options

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

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

This instructor-led live training, available both online and onsite, is designed for intermediate-level manufacturing professionals aiming to utilize AI techniques to streamline operations, minimize downtime, and foster 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.
• Deploy machine learning models to pinpoint bottlenecks and predict potential failures.
• Visualize and interpret results to facilitate data-driven decision-making.

Course Format

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

Customization Options for the Course

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

AI-driven quality control involves applying computer vision and machine learning to detect defects, anomalies, and deviations within production workflows.

This instructor-led training, available either online or onsite, is designed for beginner to intermediate quality professionals seeking to utilize AI tools for automating inspections and enhancing product quality in manufacturing settings.

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

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

Course Format

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

Customization Options

• For tailored training requests, please reach out to us to make arrangements.

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 involves using artificial intelligence 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 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 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.

Implementing AI Use Cases is a hands-on, project-based methodology for applying machine learning, computer vision, and data analytics to address real-world industrial challenges using actual or simulated datasets.

This instructor-led, live training (available online or onsite) is designed for intermediate-level cross-functional teams who want to collaboratively deploy AI solutions aligned with their operational goals and gain practical experience with industrial data pipelines.

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

• Identify and scope practical AI applications within operations, quality, or maintenance.
• Collaborate across different roles to build machine learning solutions.
• Manage, clean, and analyse diverse industrial datasets.
• Present a functional prototype of an AI-enabled solution based on a chosen application.

Course Format

• Interactive lectures and discussions.
• Group exercises and project work.
• Hands-on implementation in a live-lab environment.

Course Customization Options

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

This instructor-led, live training in Nigeria (online or onsite) is designed for cybersecurity professionals, AI engineers, and IoT developers at an advanced level who aim 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.
• Execute encryption and authentication techniques to safeguard data.
• Design resilient Edge AI architectures capable of withstanding cyber threats.
• Apply secure AI model deployment strategies within edge environments.

Cambricon MLUs (Machine Learning Units) are specialized AI chips designed to optimize inference and training for both edge devices and data center environments.

This instructor-led live training, available either online or onsite, targets intermediate developers who want to build and deploy AI models utilizing the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be able to:

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

Course Format

• Interactive lectures and discussions.
• Practical, hands-on development and deployment using BANGPy and Neuware.
• Guided exercises emphasizing optimization, integration, and testing.

Customization Options

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

Digital Twins serve as virtual representations of physical systems, augmented by live data and artificial intelligence-driven insights.

This trainer-led course, available either online or in-person, is designed for mid-level professionals looking to construct, implement, and refine digital twin models leveraging real-time data and AI-based analytics.

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

• Grasping the structure and key elements of digital twins.
• Utilising simulation software to represent complex systems and environments.
• Merging live data feeds into virtual models.
• Applying AI methods for predicting outcomes and identifying anomalies.

Course Format

• Engaging lectures and group discussions.
• Numerous exercises and practical sessions.
• Practical implementation within a live-lab setting.

Customisation Options

• For tailored training requests, please reach out to us to make arrangements.

The integration of AI into industrial computer vision is reshaping how manufacturers and quality assurance teams identify surface defects, verify part conformity, and automate visual inspection processes.

This instructor-led live training, available both online and onsite, targets intermediate to advanced-level QA teams, automation engineers, and developers who aim to design and deploy computer vision systems for defect detection and inspection using AI techniques.

Upon completing this training, participants will be equipped to:

• Comprehend the architecture and key components of industrial vision systems.
• Construct AI models for visual defect detection utilizing 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 request customized training for this course, please contact us to arrange it.

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

This instructor-led live training (available online or onsite) targets advanced 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.