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

This instructor-led, live training in India (online or onsite) is designed for 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.

The '6G and the Intelligent Edge' course offers a forward-looking perspective on how 6G wireless technologies merge with edge computing, IoT ecosystems, and AI-driven data processing to create intelligent, adaptive infrastructures with ultra-low latency.

This instructor-led live training, available both online and onsite, is tailored for intermediate-level IT architects aiming to grasp and design next-generation distributed architectures that harness the synergy between 6G connectivity and intelligent edge systems.

After completing this course, participants will be equipped to:

• Comprehend how 6G will reshape 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 facilitate intelligent decision-making.
• Plan scalable, secure, and resilient edge infrastructures ready for 6G.
• Evaluate the business and operational models empowered 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

• To request a customized training session for this course, please get in touch with us to arrange it.

This instructor-led live training in India (online or on-site) is designed for advanced-level AI practitioners, researchers, and developers who aim to master the latest Edge AI advancements, optimize their models for edge deployment, and explore specialized applications across various sectors.

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

• Investigate advanced methods for developing and optimizing Edge AI models.
• Apply cutting-edge strategies for deploying AI models on edge devices.
• Leverage specialized tools and frameworks for complex Edge AI applications.
• Enhance the performance and efficiency of Edge AI solutions.
• Explore innovative use cases and emerging trends in the Edge AI landscape.
• Tackle advanced ethical and security challenges associated with Edge AI deployments.

This instructor-led live training in India (online or onsite) targets intermediate-level developers, data scientists, and tech enthusiasts seeking practical skills in deploying AI models on edge devices for diverse applications.

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

• Comprehend the core principles of Edge AI and its advantages.
• Establish and configure the edge computing environment.
• Develop, train, and optimize AI models specifically for edge deployment.
• Deploy practical AI solutions on edge devices.
• Assess and enhance the performance of models deployed on the edge.
• Tackle ethical and security issues inherent in Edge AI applications.

AI-driven predictive maintenance leverages machine learning and data analytics to anticipate equipment failures and refine maintenance schedules. This approach shifts maintenance strategies from reactive to proactive, enhancing uptime, reducing costs, and extending asset lifespan.

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

Upon completing this training, participants will be equipped to:

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

Course Format

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

Customization Options

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

AI for Process Optimization involves leveraging machine learning and advanced data analytics to boost efficiency, enhance product quality, and increase throughput within manufacturing environments.

This instructor-led training, available both online and onsite, is designed for intermediate-level manufacturing professionals who aim to utilize AI techniques to streamline operations, minimize downtime, and foster continuous improvement.

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

• Grasp AI concepts specifically applicable to manufacturing optimization.
• Collect and prepare production data for in-depth analysis.
• Deploy machine learning models to pinpoint bottlenecks and forecast equipment failures.
• Visualize and interpret data outcomes to facilitate evidence-based decision-making.

Course Format

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

Customization Options

• For tailored training solutions, please contact us to arrange a customized session.

AI-driven Quality Control leverages computer vision and machine learning algorithms to detect defects, anomalies, and deviations within production workflows.

This instructor-led live training, available online or onsite, is designed for quality professionals ranging from beginner to intermediate levels who aim to utilize AI tools to automate inspections and enhance product quality in manufacturing settings.

Upon completing this training, participants will be capable of:

• Grasping the application of AI in industrial quality control.
• Gathering and annotating image or sensor data from production lines.
• Utilizing machine learning and computer vision for defect detection.
• Creating basic AI models for anomaly detection and yield prediction.

Course Delivery Format

• Engaging lectures combined with interactive discussions.
• Numerous exercises and practical practice sessions.
• Hands-on implementation within a live lab environment.

Customization Options for the Course

• For bespoke training arrangements, please reach out to us.

AI in Supply Chain and Manufacturing Logistics involves using 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.

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

This instructor-led live training, available both online and on-site, is designed for beginner-level decision-makers and technical leads who seek a strategic and practical overview of leveraging AI in smart factory environments.

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

• Grasping the fundamental principles of AI and machine learning.
• Recognizing key AI use cases within manufacturing and automation sectors.
• Exploring how AI facilitates predictive maintenance, quality control, and process optimization.
• Assessing the steps required to initiate AI-driven projects.

Course Format

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

Course Customization Options

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

This session offers a project-based methodology for applying machine learning, computer vision, and data analytics to address real-world industrial challenges, utilizing either live or simulated datasets.

Designed as an instructor-led, live training (available online or onsite), this program targets intermediate-level cross-functional teams aiming to collaboratively implement AI initiatives 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 domains.
• Collaborate across various roles to engineer machine learning solutions.
• Manage, cleanse, and analyze heterogeneous industrial datasets.
• Deliver a functional prototype of an AI-driven solution tailored to a specific use case.

Course Format

• Engaging lectures paired with interactive discussions.
• Team-based exercises and collaborative project work.
• Practical implementation within a live-lab environment.

Customization Options

• For bespoke training arrangements, please reach out to us.

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

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

• Grasp the security risks and vulnerabilities associated with Edge AI deployments.
• Apply encryption and authentication techniques to protect data.
• Architect resilient Edge AI systems capable of withstanding cyber threats.
• Deploy secure AI models within edge environments.

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

This instructor-led live training, available either online or on-site, targets intermediate-level developers who aim to construct and deploy AI models leveraging the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

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

• Establish and configure the development environments for BANGPy and Neuware.
• Create and optimize models using Python and C++ specifically for Cambricon MLUs.
• Deploy models onto edge and data center devices operating on the Neuware runtime.
• Integrate machine learning workflows with acceleration capabilities specific to MLUs.

Course Format

• Engaging lectures paired with interactive discussions.
• Practical, hands-on sessions involving development and deployment with BANGPy and Neuware.
• Guided exercises concentrating on optimization, integration, and testing.

Customization Options for the Course

• If you require customized training tailored to your specific Cambricon device model or use case, please get in touch with us to make the necessary arrangements.

Digital Twins serve as virtual copies of physical entities, supercharged by real-time data feeds and AI-powered analytics.

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

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

• Comprehend the architecture and key components of digital twins.
• Utilise simulation tools to model intricate systems and environments.
• Seamlessly integrate real-time data streams into virtual models.
• Apply AI methodologies for predictive analytics and anomaly detection.

Course Format

• Engaging lectures and interactive discussions.
• Numerous exercises and practical sessions.
• Hands-on implementation within a live-lab setup.

Customisation Options

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

The integration of AI with industrial computer vision is revolutionizing the way manufacturers and quality assurance (QA) teams identify surface defects, verify part conformity, and automate visual inspection workflows.

This instructor-led live training, available online or on-site, is designed for intermediate to advanced QA teams, automation engineers, and developers looking to design and implement computer vision systems for defect detection and inspection using AI methodologies.

Upon completion of 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 techniques.
• 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 seamless integration of artificial intelligence into robotic systems to enhance perception, decision-making, and autonomous control capabilities.

This instructor-led live training, available online or at your premises, 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 completing this training, participants will be equipped to:

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

Course Format

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

Customization Options

• For tailored training requirements, please reach out to us to make the necessary arrangements.