What if your AI models ran faster, trained smarter, and deployed seamlessly from edge to cloud? Huawei Ascend makes that possible.
These instructor-led courses unlock the potential of Ascend AI processors, guiding engineers through hands-on projects with MindSpore, model compression, and chip-level optimization.
Courses are delivered via online live training through an interactive remote desktop, or as onsite live training in Helsinki with labs focused on real production workloads.
Onsite sessions can be hosted at your facilities in Helsinki or arranged at a NobleProg corporate training center in Helsinki to support collaborative, team-based learning.
Also known as Ascend AI, Huawei Ascend 910, or Ascend Computing, this training helps you move beyond generic AI hardware and into purpose-built performance.
This instructor-led training in Helsinki guides intermediate AI engineers to build and optimize neural network models using the Huawei Ascend platform and CANN toolkit. Participants will configure environments, develop applications with MindSpore, and deploy to edge or cloud settings.
This instructor-led live training in Helsinki explores Huawei's AI stack, from the CANN SDK to the MindSpore framework. It helps beginners and intermediate professionals understand how these components integrate on Ascend hardware for lifecycle management and deployment.
This instructor-led training in Helsinki covers deploying and optimizing CV and NLP models using the CANN SDK for Ascend hardware. Participants will learn to convert models, integrate them into live pipelines, and enhance inference performance for real-time detection and analysis.
This instructor-led, live training in Helsinki equips advanced developers with the skills to build, deploy, and tune custom AI operators. Participants will master CANN TIK and Apache TVM integration, enabling advanced optimization and scheduling on Huawei Ascend hardware for real-world performance.
This instructor-led training in Helsinki introduces CloudMatrix for scalable AI inference. Learn to deploy, optimize, and monitor models using CANN and MindSpore. Hands-on exercises cover packaging, conversion, serving, and performance tuning for real-time and batch workloads.
This instructor-led, live training in Helsinki covers the core concepts and hands-on fundamentals of deploying AI models on Ascend edge devices using the CANN toolkit, helping participants build practical skills for compiling, optimizing, and managing constrained environments.
This live training in Helsinki introduces the CANN toolkit for AI framework developers. Learn to set up environments, convert models, and deploy applications on Ascend hardware using MindSpore, TensorFlow, or PyTorch, covering the full workflow from training to inference.
Optimize AI workloads on Ascend, Biren, and Cambricon with this hands-on training in Helsinki. Learn to benchmark models, identify bottlenecks, and apply graph, kernel, and operator-level optimizations. Tune deployment pipelines to enhance throughput and latency across these leading platforms.
Optimize neural network inference performance on Ascend AI processors with this advanced, instructor-led training in Helsinki. Explore CANN's runtime architecture, leveraging the Graph Engine, TIK, and TVM for profiling, custom operator development, and memory bottleneck resolution.
Migrate CUDA applications to Chinese GPU architectures like Huawei Ascend and Biren in Helsinki. This instructor-led course guides advanced programmers through code translation and performance optimization, covering hands-on labs for porting CUDA codebases to new SDKs.
This live training in Helsinki guides intermediate AI developers through deploying models on Ascend processors using the CANN toolkit. Learn to convert frameworks like PyTorch and TensorFlow, optimize performance, and debug issues for efficient edge and cloud inference scenarios.
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