Imagine AI models that operate with greater speed, exhibit improved training efficiency, and deploy effortlessly across the edge and cloud spectrum. Huawei Ascend enables this level of performance.
These instructor-led programs explore the capabilities of Ascend AI processors, offering engineers practical experience with MindSpore, model compression, and chip-level optimization through hands-on projects.
Training is available via online live sessions using an interactive remote desktop, or as onsite live events in Prague featuring labs tailored to real production workloads.
Onsite sessions can be conducted at your location in Prague or at a NobleProg corporate training center in Prague, designed to facilitate collaborative, team-based learning environments.
Recognized as Ascend AI, Huawei Ascend 910, or Ascend Computing, this training empowers you to move beyond standard AI hardware and achieve purpose-built performance.
From Prague Main Train Station (Praha hlavní nádraží)
Take tram 9 from Hlavní nádraží toward Sídliště Řepy.
Get off at Újezd.
Walk about 10 minutes toward Malostranské náměstí / Prokopská.
Continue along Prokopská to 296/8.
Alternative: Take the metro C from Hlavní nádraží → Muzeum, change to metro A → Malostranská, then walk across Malá Strana. This involves more walking.
From Prague Bus Station — Florenc
Take metro B from Florenc toward Zličín.
Get off at Můstek.
Change to metro A toward Nemocnice Motol.
Get off at Malostranská.
Walk approximately 10–15 minutes to Prokopská 296/8.
This instructor-led session in Prague enables intermediate AI engineers to construct and optimize neural network models using the Huawei Ascend platform and CANN toolkit. Attendees will learn to configure environments, develop applications with MindSpore, and execute deployments to edge or cloud settings.
This live, instructor-led training in Prague examines Huawei's AI stack, bridging the gap between the CANN SDK and the MindSpore framework. It empowers beginner and intermediate professionals to understand how these components interact on Ascend hardware to streamline lifecycle management and deployment.
This instructor-led training on Prague focuses on deploying and optimizing CV and NLP models using the CANN SDK for Ascend hardware. Attendees will master model conversion, integration into live pipelines, and strategies to boost inference performance for real-time detection and analysis.
This live, instructor-led training in Prague empowers advanced developers to construct, deploy, and optimize custom AI operators. Through mastering the integration of CANN TIK and Apache TVM, participants will drive advanced optimization and scheduling on Huawei Ascend hardware, ensuring robust real-world performance.
This instructor-led training on Prague provides an introduction to CloudMatrix for scalable AI inference. Participants will learn to deploy, optimize, and monitor models utilizing CANN and MindSpore. Practical exercises address packaging, conversion, serving, and performance tuning for both real-time and batch workloads.
This instructor-led live course in Prague explores the core concepts and practical fundamentals of deploying AI models on Ascend edge devices via the CANN toolkit, enabling participants to develop essential skills for compiling, optimizing, and managing constrained environments.
This live training in Prague provides an introduction to the CANN toolkit for AI framework developers. It covers setting up environments, converting models, and deploying applications on Ascend hardware using MindSpore, TensorFlow, or PyTorch, addressing the complete workflow from training to inference.
Master AI workload optimization on Ascend, Biren, and Cambricon through this practical training in Prague. Develop skills to benchmark models, pinpoint performance bottlenecks, and deploy graph, kernel, and operator-level optimizations. Refine deployment pipelines to boost throughput and latency across these premier hardware platforms.
Elevate neural network inference performance on Ascend AI processors through this advanced, instructor-led training in Prague. Delve into CANN's runtime architecture and utilize the Graph Engine, TIK, and TVM for profiling, developing custom operators, and resolving memory bottlenecks.
Migrate CUDA applications to Chinese GPU architectures such as Huawei Ascend and Biren in Prague. This instructor-led course supports advanced programmers in code translation and performance optimization, featuring hands-on labs for porting CUDA codebases to new SDKs.
This live training in Prague provides a guided pathway for intermediate AI developers looking to deploy models on Ascend processors via the CANN toolkit. It covers converting frameworks such as PyTorch and TensorFlow, along with performance optimization and debugging techniques for efficient edge and cloud inference.
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