Cambricon MLU Development with BANGPy and Neuware 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.

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.

Huawei's Ascend CANN toolkit facilitates robust AI inference on edge devices like the Ascend 310. It provides critical 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 using MindSpore Lite and AscendCL.
• Enhance model performance in environments with constrained compute and memory.
• Deploy and monitor AI applications in real-world edge scenarios.

Course Format

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

Customization Options

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

Chinese GPU architectures like Huawei Ascend, Biren, and Cambricon MLUs provide CUDA alternatives designed for local AI and high-performance computing markets.

This live training, led by an instructor (available online or onsite), is designed for advanced GPU programmers and infrastructure specialists looking to migrate and optimize their existing CUDA applications for deployment on Chinese hardware platforms.

Upon completing this training, participants will be able to:

• Assess the compatibility of current CUDA workloads with Chinese chip alternatives.
• Translate CUDA codebases into Huawei CANN, Biren SDK, and Cambricon BANGPy environments.
• Compare performance metrics and identify optimization opportunities across different platforms.
• Resolve practical challenges related to cross-architecture support and deployment.

Course Format

• Interactive lectures and discussions.
• Practical labs for code translation and performance benchmarking.
• Guided exercises focusing on multi-GPU adaptation strategies.

Course Customization Options

• To arrange customized training for this course tailored to your specific platform or CUDA project, please get in touch.

This instructor-led, live training in Kenya (online or onsite) is designed for beginner to intermediate-level agritech professionals, IoT specialists, and AI engineers interested in developing and deploying Edge AI solutions for smart farming.

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

• Understand the role of Edge AI in precision agriculture.
• Implement AI-driven crop and livestock monitoring systems.
• Develop automated irrigation and environmental sensing solutions.
• Optimize agricultural efficiency using real-time Edge AI analytics.

This live, instructor-led training delivered in Kenya (online or on-site) is designed for intermediate-level robotics engineers, autonomous vehicle developers, and AI researchers seeking 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 Kenya (online or onsite) is aimed at 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 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 Kenya (online or onsite) targets computer vision engineers, AI developers, and IoT professionals at an intermediate to advanced level who aim to implement and optimize computer vision models for real-time processing on edge devices.

Upon completing this training, participants will be able to:

• Grasp the core concepts of Edge AI and how it applies to computer vision.
• Deploy optimized deep learning models on edge devices for real-time image and video analysis.
• Utilize frameworks such as TensorFlow Lite, OpenVINO, and NVIDIA Jetson SDK for model deployment.
• Enhance AI models for better performance, power efficiency, and low-latency inference.

This instructor-led, live training in Kenya (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 Kenya (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 live, instructor-led training in Kenya (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:

• Understand the role of Edge AI in industrial automation.
• Implement predictive maintenance solutions using Edge AI.
• Apply AI techniques for quality control in manufacturing processes.
• Optimize industrial processes using Edge AI.
• Deploy and manage Edge AI solutions in industrial environments.

Ascend, Biren, and Cambricon represent some of the foremost AI hardware solutions in China, providing distinct acceleration capabilities and profiling utilities tailored for large-scale AI production environments.

This live, instructor-led training session, available both online and onsite, is designed for advanced AI infrastructure and performance engineers seeking to enhance model inference and training workflows across various Chinese AI chip ecosystems.

Upon completion of this course, participants will gain the ability to:

• Conduct benchmarks for models on Ascend, Biren, and Cambricon platforms.
• Pinpoint system bottlenecks and identify inefficiencies in memory and computing resources.
• Implement optimizations at the graph, kernel, and operator levels.
• Refine deployment pipelines to achieve better throughput and reduced latency.

Course Format

• Interactive lectures combined with discussions.
• Practical application of profiling and optimization tools across each respective platform.
• Guided exercises centered on real-world tuning scenarios.

Customization Opportunities

• For customized training aligned with your specific performance environment or model architecture, please reach out to us to make arrangements.