Austin, TX – Regus at Dobie Center

2021 Guadalupe Street, Suite 260, Austin, United States, 78705

The venue is located in the vibrant West Campus neighborhood near the University of Texas at the Dobie Center, easily reachable by car via I‑35 or I‑35 Frontage Road and Loop 1, with on-site and street parking nearby. From Austin–Bergstrom International Airport (AUS), about 11 miles southeast, a taxi or rideshare takes around 20–25 minutes via TX‑71 West and I‑35 North. Public transit users can take Capital Metro routes to the University of Texas/Dobie Mall stop directly in front of the building, placing it within a short walk for attendees without cars.

Austin, TX - Regus - Littlefield Congress

106 E 6th St, Austin, United States, 78701

The venue is conveniently situated near I‑35 and US‑183, making it easily accessible by car, with both public and garage parking options—such as the Littlefield Garage at 508 Brazos—located within walking distance. For those using public transportation, the venue is just a short walk from the Downtown Station (CapMetro) and is served by several bus routes. Travelers arriving by air will find that Austin-Bergstrom International Airport is approximately 8 miles away, providing straightforward access to and from the venue.

Explore Our Courses

Developing AI Applications with Huawei Ascend and CANN

 21 Hours

Huawei Ascend is a family of AI processors designed for high-performance inference and training.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI engineers and data scientists who wish to develop and optimize neural network models using Huawei’s Ascend platform and the CANN toolkit.

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

  • Set up and configure the CANN development environment.
  • Develop AI applications using MindSpore and CloudMatrix workflows.
  • Optimize performance on Ascend NPUs using custom operators and tiling.
  • Deploy models to edge or cloud environments.

Format of the Course

  • Interactive lecture and discussion.
  • Hands-on use of Huawei Ascend and CANN toolkit in sample applications.
  • Guided exercises focused on model building, training, and deployment.

Course Customization Options

  • To request a customized training for this course based on your infrastructure or datasets, please contact us to arrange.
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Understanding Huawei’s AI Compute Stack: From CANN to MindSpore

 14 Hours

Huawei’s AI stack — from the low-level CANN SDK to the high-level MindSpore framework — offers a tightly integrated AI development and deployment environment optimized for Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at beginner-level to intermediate-level technical professionals who wish to understand how the CANN and MindSpore components work together to support AI lifecycle management and infrastructure decisions.

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

  • Understand the layered architecture of Huawei’s AI compute stack.
  • Identify how CANN supports model optimization and hardware-level deployment.
  • Evaluate the MindSpore framework and toolchain in relation to industry alternatives.
  • Position Huawei's AI stack within enterprise or cloud/on-prem environments.

Format of the Course

  • Interactive lecture and discussion.
  • Live system demos and case-based walkthroughs.
  • Optional guided labs on model flow from MindSpore to CANN.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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CANN SDK for Computer Vision and NLP Pipelines

 14 Hours

The CANN SDK (Compute Architecture for Neural Networks) provides powerful deployment and optimization tools for real-time AI applications in computer vision and NLP, especially on Huawei Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI practitioners who wish to build, deploy, and optimize vision and language models using the CANN SDK for production use cases.

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

  • Deploy and optimize CV and NLP models using CANN and AscendCL.
  • Use CANN tools to convert models and integrate them into live pipelines.
  • Optimize inference performance for tasks like detection, classification, and sentiment analysis.
  • Build real-time CV/NLP pipelines for edge or cloud-based deployment scenarios.

Format of the Course

  • Interactive lecture and demonstration.
  • Hands-on lab with model deployment and performance profiling.
  • Live pipeline design using real CV and NLP use cases.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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Building Custom AI Operators with CANN TIK and TVM

 14 Hours

CANN TIK (Tensor Instruction Kernel) and Apache TVM enable advanced optimization and customization of AI model operators for Huawei Ascend hardware.

This instructor-led, live training (online or onsite) is aimed at advanced-level system developers who wish to build, deploy, and tune custom operators for AI models using CANN’s TIK programming model and TVM compiler integration.

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

  • Write and test custom AI operators using the TIK DSL for Ascend processors.
  • Integrate custom ops into the CANN runtime and execution graph.
  • Use TVM for operator scheduling, auto-tuning, and benchmarking.
  • Debug and optimize instruction-level performance for custom computation patterns.

Format of the Course

  • Interactive lecture and demonstration.
  • Hands-on coding of operators using TIK and TVM pipelines.
  • Testing and tuning on Ascend hardware or simulators.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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CANN for Edge AI Deployment

 14 Hours

Huawei's Ascend CANN toolkit enables powerful AI inference on edge devices such as the Ascend 310. CANN provides essential tools for compiling, optimizing, and deploying models where compute and memory are constrained.

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

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

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

Format of the Course

  • Interactive lecture and demonstration.
  • Hands-on lab work with edge-specific models and scenarios.
  • Live deployment examples on virtual or physical edge hardware.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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Introduction to CANN for AI Framework Developers

 7 Hours

CANN (Compute Architecture for Neural Networks) is Huawei’s AI computing toolkit used to compile, optimize, and deploy AI models on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at beginner-level AI developers who wish to understand how CANN fits into the model lifecycle from training to deployment, and how it works with frameworks like MindSpore, TensorFlow, and PyTorch.

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

  • Understand the purpose and architecture of the CANN toolkit.
  • Set up a development environment with CANN and MindSpore.
  • Convert and deploy a simple AI model to Ascend hardware.
  • Gain foundational knowledge for future CANN optimization or integration projects.

Format of the Course

  • Interactive lecture and discussion.
  • Hands-on labs with simple model deployment.
  • Step-by-step walkthrough of the CANN toolchain and integration points.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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Optimizing Neural Network Performance with CANN SDK

 14 Hours

CANN SDK (Compute Architecture for Neural Networks) is Huawei’s AI compute foundation that allows developers to fine-tune and optimize the performance of deployed neural networks on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at advanced-level AI developers and system engineers who wish to optimize inference performance using CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator development.

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

  • Understand CANN's runtime architecture and performance lifecycle.
  • Use profiling tools and Graph Engine for performance analysis and optimization.
  • Create and optimize custom operators using TIK and TVM.
  • Resolve memory bottlenecks and improve model throughput.

Format of the Course

  • Interactive lecture and discussion.
  • Hands-on labs with real-time profiling and operator tuning.
  • Optimization exercises using edge-case deployment examples.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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Deploying AI Models with CANN and Ascend AI Processors

 14 Hours

CANN (Compute Architecture for Neural Networks) is Huawei’s AI compute stack for deploying and optimizing AI models on Ascend AI processors.

This instructor-led, live training (online or onsite) is aimed at intermediate-level AI developers and engineers who wish to deploy trained AI models efficiently to Huawei Ascend hardware using the CANN toolkit and tools such as MindSpore, TensorFlow, or PyTorch.

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

  • Understand the CANN architecture and its role in the AI deployment pipeline.
  • Convert and adapt models from popular frameworks to Ascend-compatible formats.
  • Use tools like ATC, OM model conversion, and MindSpore for edge and cloud inference.
  • Diagnose deployment issues and optimize performance on Ascend hardware.

Format of the Course

  • Interactive lecture and demonstration.
  • Hands-on lab work using CANN tools and Ascend simulators or devices.
  • Practical deployment scenarios based on real-world AI models.

Course Customization Options

  • To request a customized training for this course, please contact us to arrange.
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Upcoming Courses

Developing AI Applications with Huawei Ascend and CANN

2025-08-18 9:30 am
21 hours
Austin, TX - Regus - Littlefield Congress
$ 4054 (Online)
$ 4054 (Classroom)

Introduction to CANN for AI Framework Developers

2025-08-29 9:30 am
7 hours
Austin, TX – Regus at Dobie Center
$ 1630 (Online)
$ 1630 (Classroom)

Optimizing Neural Network Performance with CANN SDK

2025-09-15 9:30 am
14 hours
Austin, TX - Regus - Littlefield Congress
$ 2703 (Online)
$ 2703 (Classroom)

Building Custom AI Operators with CANN TIK and TVM

2025-09-29 9:30 am
14 hours
Austin, TX – Regus at Dobie Center
$ 2703 (Online)
$ 2703 (Classroom)

Deploying AI Models with CANN and Ascend AI Processors

2025-10-13 9:30 am
14 hours
Austin, TX - Regus - Littlefield Congress
$ 2703 (Online)
$ 2703 (Classroom)

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These courses are also available in other countries

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