Huawei Ascend Training in Massachusetts

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 Massachusetts with labs focused on real production workloads.

Onsite sessions can be hosted at your facilities in Massachusetts or arranged at a NobleProg corporate training center in Massachusetts 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.

NobleProg – Your Local Training Provider

NobleProg Training Place, City Boston, MA – Regus at Federal Street

101 Federal St, Suite 1900, Boston, United States, 02110

The venue is located in the heart of Boston’s Financial District on Federal Street, easily accessible by car via I‑90, I‑93, and I‑95 with numerous nearby parking garages. From Logan International Airport (BOS), a taxi or rideshare takes approximately 20–25 minutes via I‑93 North. Public transit is seamless: the 15th Street and South Station – Financial District stops on MBTA's Red, Orange, and Silver lines are within a few minutes’ walk, and multiple bus routes traverse Federal and Congress Streets.

NobleProg Training Place, City Burlington, MA – Regus at The District

1500 District Avenue, Burlington, United States, 01803

The venue is located within The District business campus at 1500 District Avenue, easily accessed by car via I‑89 or US‑3 with free on-site parking and additional municipal lots. From Boston’s Logan International Airport (BOS), approximately 15 miles southeast, a taxi or rideshare takes 25–30 minutes via I‑93 North and I‑95 North. Public transit is served by MBTA commuter rail to South Burlington, with the Campus Parkway #2 bus running directly past the entrance—placing the venue within a short walk for attendees without cars.

NobleProg Training Place, City Cambridge, MA – Regus at Harvard Square

One Mifflin Place, Suite 400, Cambridge, United States, 02138

The venue is ideally situated in the heart of Harvard Square at One Mifflin Place, easily accessed by car via Route 2, MA‑2A, or Memorial Drive, with pay-to-park garages and metered street spaces nearby. From Boston Logan International Airport (BOS), taxis or rideshares take approximately 25–30 minutes via I‑90 West and Cambridge Street. Alternatively, public transit offers seamless connections: take the MBTA Red Line to Harvard station, and the entrance is a 3-minute walk from the square, providing effortless access for attendees without cars.

NobleProg Training Place, City Worcester, MA – Regus at Campus Square

370 Main Street, Worcester, United States, 01608

The venue is located in the LEED Gold–certified Campus Square building at 370 Main Street in the heart of Worcester, easily reachable by car via I‑290 or I‑90, with abundant on-site parking and municipal garages nearby. From Worcester Regional Airport (ORH), about 5 miles west, a taxi or rideshare takes 10–15 minutes via Airport Drive and Main Street. Public transit is seamless: multiple WRTA bus routes stop just outside the building, and Worcester Amtrak/MBTA train station is an easy 12-minute walk, allowing easy access without a car.

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Explore Our Courses

Developing AI Applications with Huawei Ascend and CANN

21 Hours

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

14 Hours

CANN SDK for Computer Vision and NLP Pipelines

14 Hours

Building Custom AI Operators with CANN TIK and TVM

14 Hours

AI Inference and Deployment with CloudMatrix

21 Hours

CANN for Edge AI Deployment

14 Hours

Introduction to CANN for AI Framework Developers

7 Hours

Performance Optimization on Ascend, Biren, and Cambricon

21 Hours

Optimizing Neural Network Performance with CANN SDK

14 Hours

Migrating CUDA Applications to Chinese GPU Architectures

21 Hours

Deploying AI Models with CANN and Ascend AI Processors

14 Hours

Last Updated: 2025-07-23