Edge AI for Computer Vision: Real-Time Image Processing 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.

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.

Huawei's Ascend CANN toolkit empowers robust AI inference on edge devices like the Ascend 310. It offers crucial tools for compiling, optimizing, and deploying models in environments where computing power and memory are limited.

This instructor-led, live training (available online or onsite) is designed for intermediate-level AI developers and integrators who aim to deploy and optimize models on Ascend edge devices using the CANN toolchain.

Upon completing this training, participants will be able to:

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines with MindSpore Lite and AscendCL.
• Enhance model performance within constrained compute and memory settings.
• Deploy and monitor AI applications in real-world edge scenarios.

Format of the Course

• Interactive lectures and demonstrations.
• Hands-on lab exercises featuring edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Course Customization Options

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

This instructor-led, live training in Nigeria (available online or on-site) targets beginner to intermediate-level agritech professionals, IoT specialists, and AI engineers who aim to develop and deploy Edge AI solutions for smart farming.

Upon completing this training, participants will be equipped to:

• Grasp the role of Edge AI in precision agriculture.
• Deploy AI-driven systems for monitoring crops and livestock.
• Create automated irrigation and environmental sensing solutions.
• Enhance agricultural efficiency through real-time Edge AI analytics.

This instructor-led, live training in Nigeria (online or onsite) is aimed at intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers who wish to leverage Edge AI for innovative autonomous system solutions.

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

• Understand the role and benefits of Edge AI in autonomous systems.
• Develop and deploy AI models for real-time processing on edge devices.
• Implement Edge AI solutions in autonomous vehicles, drones, and robotics.
• Design and optimize control systems using Edge AI.
• Address ethical and regulatory considerations in autonomous AI applications.

This instructor-led, live training in Nigeria (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI, from conceptual foundations to practical implementation, including setup and deployment.

Upon completing this training, participants will be able to:

• Grasp the fundamental concepts of Edge AI.
• Set up and configure Edge AI environments.
• Develop, train, and optimize Edge AI models.
• Deploy and manage Edge AI applications.
• Integrate Edge AI with existing systems and workflows.
• Address ethical considerations and best practices in Edge AI implementation.

This instructor-led live training in Nigeria (online or onsite) is targeted at beginner-level law enforcement personnel who wish to move from manual facial sketching to using AI tools for developing facial recognition systems.

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

• Understand the fundamentals of Artificial Intelligence and Machine Learning.
• Learn the basics of digital image processing and its application in facial recognition.
• Develop skills in using AI tools and frameworks to create facial recognition models.
• Gain hands-on experience in creating, training, and testing facial recognition systems.
• Understand ethical considerations and best practices in the use of facial recognition technology.

Fiji is a powerful open-source image processing package that bundles ImageJ (a program designed for scientific multidimensional images) along with a comprehensive suite of plugins for scientific image analysis.

In this instructor-led, live training, participants will learn how to leverage the Fiji distribution and its underlying ImageJ program to create robust image analysis applications.

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

• Use Fiji's advanced programming features and software components to extend ImageJ capabilities
• Stitch large 3D images from overlapping tiles
• Automate the update of a Fiji installation on startup using the integrated update system
• Select from a broad selection of scripting languages to build custom image analysis solutions
• Utilize Fiji's powerful libraries, such as ImgLib, to process large bioimage datasets efficiently
• Deploy applications and collaborate effectively with other scientists on similar projects

Format of the Course

• Interactive lecture and discussion
• Extensive exercises and practical application
• Hands-on implementation in a live-lab environment

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) is aimed at beginner to intermediate researchers and laboratory professionals who want to process and analyze images related to histological tissues, blood cells, algae, and other biological samples.

Upon completing this training, participants will be able to:

• Navigate the Fiji interface and make effective use of ImageJ’s core functions.
• Preprocess and enhance scientific images to improve analysis outcomes.
• Perform quantitative image analysis, including cell counting and area measurement.
• Automate repetitive tasks using macros and plugins.
• Customize workflows to meet specific image analysis requirements in biological research.

This instructor-led, live training in Nigeria (online or onsite) is aimed at software engineers who wish to program in Python with OpenCV 4 for deep learning.

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

• View, load, and classify images and videos using OpenCV 4.
• Implement deep learning in OpenCV 4 with TensorFlow and Keras.
• Run deep learning models and generate impactful reports from images and videos.

This instructor-led live training, available in Nigeria (online or onsite), is aimed at intermediate-level professionals who wish to use Vision Builder AI to design, implement, and optimise automated inspection systems for SMT (Surface-Mount Technology) processes.

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

• Set up and configure automated inspections using Vision Builder AI.
• Acquire and preprocess high-quality images for analysis.
• Implement logic-based decisions for defect detection and process validation.
• Generate inspection reports and optimise system performance.