Deploying AI Models on Edge Devices with NVIDIA Jetson Training Course

This instructor-led, live training in South Africa (online or onsite) is designed for intermediate-level telecom professionals, AI engineers, and IoT specialists keen on 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 ensure efficient performance on edge devices.

The '6G and the Intelligent Edge' course offers a forward-looking exploration into the convergence of 6G wireless technologies, edge computing, IoT ecosystems, and AI-driven data processing. This integration is designed to support intelligent, low-latency, and adaptive infrastructures.

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

Upon completing this course, participants will be equipped to:

• Comprehend how 6G will transform edge computing and IoT architectures.
• Design distributed systems tailored for 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 enabled by the convergence of 6G and edge technologies.

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

This instructor-led, live training in South Africa (online or onsite) is aimed at advanced-level AI practitioners, researchers, and developers who wish to master the latest advancements in Edge AI, optimise their AI models for edge deployment, and explore specialised applications across various industries.

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

• Explore advanced techniques in Edge AI model development and optimisation.
• Implement cutting-edge strategies for deploying AI models on edge devices.
• Utilise specialised tools and frameworks for advanced Edge AI applications.
• Optimise 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 South Africa (online or onsite) is designed for intermediate-level developers, data scientists, and technology enthusiasts who wish to acquire practical skills in deploying AI models on edge devices for a variety of applications.

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

• Grasp the principles of Edge AI and its associated benefits.
• Set up and configure an edge computing environment.
• Develop, train, and optimise AI models for edge deployment.
• Implement practical AI solutions on edge devices.
• Evaluate and enhance the performance of models deployed on the edge.
• Address ethical and security considerations in Edge AI applications.

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

Upon completing this training, participants will be able to:

• Identify security risks and vulnerabilities within Edge AI deployments.
• Implement encryption and authentication techniques to protect data.
• Design resilient Edge AI architectures capable of withstanding cyber threats.
• Apply secure strategies for deploying AI models in edge environments.

Cambricon MLUs (Machine Learning Units) are purpose-built AI processors designed to enhance inference and training capabilities in both edge computing and data centre environments.

This instructor-led live training, available either online or onsite, is tailored for intermediate developers looking to construct and deploy AI models leveraging the BANGPy framework and Neuware SDK on Cambricon MLU hardware.

Upon completing this training, participants will be equipped to:

• Configure and set up development environments for BANGPy and Neuware.
• Develop and refine Python and C++ models optimised for Cambricon MLUs.
• Deploy models onto edge and data centre devices running the Neuware runtime.
• Integrate machine learning workflows with MLU-specific acceleration features.

Course Format

• Interactive lectures and discussions.
• Practical application of BANGPy and Neuware for development and deployment.
• Guided exercises centred on optimization, integration, and testing.

Customisation Options

• To arrange bespoke training for this course, tailored to your specific Cambricon device model or use case, please contact us directly.

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

This instructor-led live training (available online or onsite) targets intermediate-level AI developers and integrators who want to deploy and optimise models on Ascend edge devices using the CANN toolchain.

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

• Prepare and convert AI models for the Ascend 310 using CANN tools.
• Construct lightweight inference pipelines using MindSpore Lite and AscendCL.
• Optimise model performance for constrained compute and memory environments.
• Deploy and monitor AI applications in real-world edge use cases.

Course Format

• Interactive lectures and demonstrations.
• Practical lab work involving edge-specific models and scenarios.
• Live deployment examples on virtual or physical edge hardware.

Course Customisation Options

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

This instructor-led, live training in South Africa (online or onsite) is designed for agritech professionals, IoT specialists, and AI engineers at beginner to intermediate levels who aim to develop and deploy Edge AI solutions for smart farming.

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

• Comprehend 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 South Africa (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 South Africa (online or onsite) is designed for intermediate-level developers and IT professionals who wish to gain a comprehensive understanding of Edge AI from concept to practical implementation, including setup and deployment.

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

• Understand the fundamental concepts of Edge AI.
• Set up and configure Edge AI environments.
• Develop, train, and optimise 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 South Africa (online or onsite) targets intermediate to advanced computer vision engineers, AI developers, and IoT professionals who wish to implement and optimise computer vision models for real-time processing on edge devices.

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

• Grasp the fundamentals of Edge AI and its applications in computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Utilise frameworks such as TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Optimise AI models for performance, power efficiency, and low-latency inference.

This instructor-led, live training in South Africa (online or onsite) is aimed at intermediate-level finance professionals, fintech developers, and AI specialists who wish to implement Edge AI solutions in financial services.

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

• Understand the role of Edge AI in financial services.
• Implement fraud detection systems using Edge AI.
• Enhance customer service through AI-driven solutions.
• Apply Edge AI for risk management and decision-making.
• Deploy and manage Edge AI solutions in financial environments.

This instructor-led, live training in South Africa (online or onsite) is aimed at intermediate-level healthcare professionals, biomedical engineers, and AI developers who wish to leverage Edge AI for innovative healthcare solutions.

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

• Understand the role and benefits of Edge AI in healthcare.
• Develop and deploy AI models on edge devices for healthcare applications.
• Implement Edge AI solutions in wearable devices and diagnostic tools.
• Design and deploy patient monitoring systems using Edge AI.
• Address ethical and regulatory considerations in healthcare AI applications.

This instructor-led, live training in South Africa (online or onsite) is aimed at intermediate-level industrial engineers, manufacturing professionals, and AI developers who wish to implement Edge AI solutions in industrial automation.

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

• Grasp the significance of Edge AI within industrial automation.
• Deploy predictive maintenance solutions leveraging Edge AI.
• Utilise AI methods for quality assurance in manufacturing workflows.
• Enhance industrial processes through Edge AI.
• Roll out and oversee Edge AI solutions in industrial environments.

This instructor-led, live training in South Africa (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

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

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.