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

This instructor-led live training in Kenya (online or onsite) is aimed at intermediate-level telecom professionals, AI engineers, and IoT specialists who wish to explore how 5G networks accelerate Edge AI applications.

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

• Understand the fundamentals of 5G technology and its impact on Edge AI.
• Deploy AI models optimized for low-latency applications in 5G environments.
• Implement real-time decision-making systems using 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:

• Grasp how 6G will revolutionize edge computing and IoT architectures.
• Architect distributed systems tailored for ultra-low latency, high bandwidth, and autonomous operations.
• Incorporate AI and data analytics at the edge to enable intelligent decision-making.
• Plan scalable, secure, and resilient 6G-ready edge infrastructures.
• Assess 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 Kenya (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 Kenya (online or onsite) is aimed at intermediate-level developers, data scientists, and technology 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 streamline maintenance schedules. This approach shifts maintenance strategies from reactive to proactive, resulting in improved operational uptime, reduced costs, and extended asset life.

This instructor-led live training, available online or on-site, targets intermediate-level professionals looking to deploy AI-led predictive maintenance solutions within industrial settings.

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

• Grasping the distinctions between predictive maintenance and reactive or preventive strategies.
• Gathering and organizing machine data for AI-led analysis.
• Utilizing machine learning models to identify anomalies and forecast failures.
• Executing complete workflows that transform sensor data into actionable insights.

Course Format

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

Course Customization Options

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

AI-driven Process Optimization involves utilizing machine learning and advanced data analytics to boost efficiency, enhance product quality, and increase throughput within manufacturing operations.

This instructor-led live training, available both online and onsite, targets intermediate-level manufacturing professionals eager to apply AI techniques to streamline operations, minimize downtime, and drive continuous improvement.

Upon completing this training, participants will be equipped to:

• Grasp AI concepts pertinent to manufacturing optimization.
• Gather and prepare production data for comprehensive analysis.
• Deploy machine learning models to detect bottlenecks and forecast equipment failures.
• Visualize and interpret data insights to facilitate informed, data-driven decision-making.

Course Delivery Format

• Interactive lectures coupled with group discussions.
• Ample exercises and practical practice sessions.
• Hands-on implementation exercises within a live laboratory environment.

Customization Options

• For customized training arrangements, please reach out to us to discuss your specific requirements.

Artificial Intelligence for Quality Control leverages computer vision and machine learning methodologies to pinpoint defects, irregularities, and deviations within production workflows.

This instructor-led training, available either online or on-site, is designed for quality professionals at the beginner to intermediate level who aim to utilise AI tools to automate inspection processes and enhance product quality in manufacturing settings.

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

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

Course Format

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

Course Customization Options

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

Leveraging AI in Supply Chain and Manufacturing Logistics involves applying predictive analytics, machine learning, and automation to optimize inventory management, routing efficiency, and 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, enhance demand forecasting accuracy, and automate warehouse and transport operations.

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

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

Format of the Course

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

Course Customization Options

• For customized training requests, please contact us to make arrangements.

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

This instructor-led training session, available both online and onsite, is designed for beginner-level decision-makers and technical leads who seek a strategic and practical introduction to leveraging AI in smart factory environments.

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

• Comprehend the fundamental principles of artificial intelligence and machine learning.
• Identify key AI applications in manufacturing and automation sectors.
• Explore how AI facilitates predictive maintenance, quality control, and process optimization.
• Evaluate the necessary steps for initiating AI-driven projects.

Course Format

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

Course Customization Options

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

AI Use Case Implementation offers a hands-on, project-focused methodology for leveraging machine learning, computer vision, and data analytics to address real-world industrial challenges, utilizing actual or simulated datasets.

This instructor-led live training, available both online and onsite, is designed for intermediate-level cross-functional teams aiming to collaboratively deploy AI solutions that align 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 functions.
• Collaborate effectively across different roles to build machine learning solutions.
• Manage, clean, and analyze varied industrial datasets.
• Demonstrate a functional prototype of an AI-driven solution based on a selected use case.

Course Format

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

Customization Options for the Course

• For tailored training on this course, please reach out to us to make arrangements.

This instructor-led, live training in Kenya (online or onsite) is designed for advanced cybersecurity professionals, AI engineers, and IoT developers aiming to establish strong security measures and resilience strategies within Edge AI systems.

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

• Identify security risks and vulnerabilities inherent in Edge AI deployments.
• Deploy encryption and authentication methods to protect data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Execute secure AI model deployment strategies tailored for edge environments.

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

This instructor-led live training, available online or on-site, targets intermediate developers looking to build and deploy AI models using 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 for Cambricon MLUs.
• Deploy models to edge and data center devices running the Neuware runtime.
• Integrate machine learning workflows with MLU-specific acceleration capabilities.

Course Format

• Interactive lectures and discussions.
• Hands-on practice with BANGPy and Neuware for development and deployment.
• Guided exercises focusing on optimization, integration, and testing.

Customization Options

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

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.

Course Delivery Structure

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Options for Tailoring the Course

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

Artificial intelligence-powered industrial computer vision is revolutionizing the way manufacturers and quality assurance 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 quality assurance teams, automation engineers, and developers eager to design and implement computer vision systems for defect detection and inspection using AI techniques.

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

• Grasping the architecture and key components of industrial vision systems.
• Developing AI models for visual defect detection using deep learning.
• Integrating real-time inspection pipelines with industrial cameras and devices.
• Deploying and optimizing AI-enabled inspection systems within production environments.

Course Format

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

Customization Options

• For tailored training requests, please contact us to arrange.

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 onsite, is designed for advanced robotics engineers, systems integrators, and automation leads who aim to implement AI-driven perception, planning, and control within smart manufacturing settings.

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

• Grasp and apply AI techniques for robotic perception and sensor fusion.
• Create motion planning algorithms for both collaborative and industrial robots.
• Implement learning-based control strategies to facilitate real-time decision-making.
• Seamlessly integrate intelligent robotic systems into smart factory workflows.

Course Format

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

Course Customization Options

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