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

The Huawei Ascend family of AI processors is 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 for government applications.

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

  • Set up and configure the CANN development environment for government use.
  • Develop AI applications using MindSpore and CloudMatrix workflows tailored for public sector needs.
  • Optimize performance on Ascend NPUs using custom operators and tiling, ensuring alignment with government standards.
  • Deploy models to edge or cloud environments, adhering to government security protocols.

Format of the Course

  • Interactive lecture and discussion focusing on government-specific use cases.
  • Hands-on use of Huawei Ascend and CANN toolkit in sample applications relevant to public sector workflows.
  • Guided exercises focused on model building, training, and deployment for government projects.

Course Customization Options

  • To request a customized training for this course based on your infrastructure or datasets specific to government operations, 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 technical professionals with beginner to intermediate levels of expertise who wish to understand how the CANN and MindSpore components work together to support AI lifecycle management and infrastructure decisions for government.

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 for government use.

Format of the Course

  • Interactive lecture and discussion.
  • Live system demonstrations 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 robust deployment and optimization tools for real-time artificial intelligence applications in computer vision and natural language processing, particularly on Huawei Ascend hardware.

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

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

  • Deploy and optimize computer vision (CV) and natural language processing (NLP) models using CANN and AscendCL.
  • Utilize CANN tools to convert models and integrate them into operational pipelines.
  • Enhance inference performance for tasks such as detection, classification, and sentiment analysis.
  • Develop real-time CV/NLP pipelines for edge or cloud-based deployment scenarios in public sector environments.

Format of the Course

  • Interactive lecture and demonstration.
  • Hands-on laboratory with model deployment and performance profiling.
  • Live pipeline design using real-world CV and NLP use cases for government applications.

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 for government applications.

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 operations 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 facilitates robust AI inference on edge devices such as the Ascend 310. CANN offers essential tools for compiling, optimizing, and deploying models in environments with limited compute and memory resources.

This instructor-led, live training (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 for government applications.

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

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

Format of the Course

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

Course Customization Options

  • To request a customized training for this course, please contact Govtra 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 designed for compiling, optimizing, and deploying 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 integrates with frameworks such as MindSpore, TensorFlow, and PyTorch for government applications.

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 for government use.
  • Convert and deploy a simple AI model to Ascend hardware.
  • Gain foundational knowledge for future CANN optimization or integration projects in public sector workflows.

Format of the Course

  • Interactive lecture and discussion focused on government applications.
  • Hands-on labs with simple model deployment for government use cases.
  • Step-by-step walkthrough of the CANN toolchain and integration points relevant to public sector workflows.

Course Customization Options

  • To request a customized training for this course, please contact Govtra 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 designed to enable 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 enhance inference performance using CANN’s advanced toolset, including the Graph Engine, TIK, and custom operator development for government applications.

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

  • Understand CANN's runtime architecture and performance lifecycle for government use cases.
  • Utilize profiling tools and Graph Engine for performance analysis and optimization in public sector environments.
  • Create and optimize custom operators using TIK and TVM, ensuring alignment with government standards.
  • Address memory bottlenecks and improve model throughput to meet the demands of government workflows.

Format of the Course

  • Interactive lecture and discussion focused on government applications.
  • Hands-on labs with real-time profiling and operator tuning tailored for government scenarios.
  • Optimization exercises using edge-case deployment examples relevant to public sector operations.

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 designed 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 efficiently deploy trained AI models to Huawei Ascend hardware using the CANN toolkit and tools such as MindSpore, TensorFlow, or PyTorch. The course is tailored for government professionals seeking to enhance their technical capabilities in AI deployment.

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

  • Understand the CANN architecture and its role in the AI deployment pipeline for government applications.
  • Convert and adapt models from popular frameworks to Ascend-compatible formats suitable for use in public sector environments.
  • Utilize tools like ATC, OM model conversion, and MindSpore for edge and cloud inference in governmental workflows.
  • Diagnose deployment issues and optimize performance on Ascend hardware to meet the rigorous standards of government operations.

Format of the Course

  • Interactive lecture and demonstration tailored for government participants.
  • Hands-on lab work using CANN tools and Ascend simulators or devices, designed to meet the specific needs of public sector professionals.
  • Practical deployment scenarios based on real-world AI models relevant to government operations.

Course Customization Options

  • To request a customized training for this course, tailored specifically for government agencies, please contact us to arrange.
Read more...

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Upcoming Courses

CANN for Edge AI Deployment

2026-01-08 09:30
14 hours
Austin, TX – Regus at Dobie Center
$ 2703 (Online)
$ 2703 (Classroom)

CANN for Edge AI Deployment

2026-01-22 09:30
14 hours
Austin, TX - Regus - Littlefield Congress
$ 2703 (Online)
$ 2703 (Classroom)

Optimizing Neural Network Performance with CANN SDK

2026-02-05 09:30
14 hours
Austin, TX – Regus at Dobie Center
$ 2703 (Online)
$ 2703 (Classroom)

Understanding Huawei’s AI Compute Stack: From CANN to MindSpore

2026-02-19 09:30
14 hours
Austin, TX - Regus - Littlefield Congress
$ 2703 (Online)
$ 2703 (Classroom)

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