GPU Programming on Biren AI Accelerators Training Course

This instructor-led course in Taiwan provides an introduction to CloudMatrix for scalable AI inference. You will learn to deploy, optimize, and monitor models using CANN and MindSpore. The hands-on exercises focus on packaging, conversion, serving, and performance tuning for both real-time and batch workloads.

This instructor-led, live training in Taiwan (online or onsite) targets beginner to intermediate-level AI engineers and software developers seeking a foundational understanding of AI engineering principles and practices.

Upon completion, participants will be able to:

• Grasp the core concepts and technologies driving AI and machine learning.
• Build fundamental machine learning models using TensorFlow and PyTorch.
• Apply AI methods to resolve practical issues in software development.
• Oversee and sustain AI projects through proven engineering best practices.
• Acknowledge the ethical implications and responsibilities associated with AI system development.

This two-day, hands-on program empowers participants with the practical skills needed to leverage Generative AI tools effectively, securely, and consistently within technical and operational workflows. The training emphasizes integrating AI as a dependable daily companion for drafting and refining documentation, organizing requirements, expediting analysis and reporting, aiding in problem-solving, and enhancing cross-functional communication. Attendees will acquire established prompting strategies, validation methods to minimize errors and 'hallucinations,' and streamlined governance protocols to safeguard confidential data and intellectual property. The course is structured to deliver immediately applicable templates, workflows, and a sustainable approach to AI-assisted work.

This instructor-led, live training in Taiwan (online or onsite) is tailored for intermediate to advanced AI professionals and software developers aiming to build intelligent applications using AI and ML.

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

• Understand the advanced concepts and technologies behind AI and ML.
• Analyze and visualize data to inform AI/ML model development.
• Build, train, and deploy AI/ML models effectively.
• Create intelligent applications that can solve real-world problems.
• Evaluate the ethical implications of AI applications in various industries.

Transition CUDA applications to Chinese GPU architectures such as Huawei Ascend and Biren within Taiwan. This instructor-led course assists advanced developers in executing code translation and performance refinement, featuring practical labs for adapting CUDA codebases to emerging SDKs.

This instructor-led, live training in Taiwan (online or onsite) is designed for beginner-level IT professionals who seek a foundational understanding of intelligent applications and their diverse industrial applications.

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

• Comprehend the history, core principles, and societal impact of artificial intelligence.
• Identify and implement various machine learning algorithms.
• Effectively manage and analyze data for AI-driven applications.
• Recognize the practical use cases and limitations of AI within different sectors.
• Discuss the ethical considerations and societal implications associated with AI technology.

This instructor-led, live training in Taiwan (online or onsite) targets intermediate to advanced data scientists, engineers, and AI practitioners who wish to master the intricacies of intelligent applications and leverage them to solve complex, real-world problems.

Upon completion of this training, participants will be equipped to:

• Implement and evaluate deep learning architectures.
• Deploy machine learning solutions at scale within distributed computing environments.
• Design and implement reinforcement learning models for strategic decision-making.
• Build advanced NLP systems for language comprehension.
• Employ computer vision methodologies for image and video analysis.
• Navigate ethical considerations in the development and deployment of AI systems.

Maximize AI workload performance on Ascend, Biren, and Cambricon through this practical training in Taiwan. Master the skills to benchmark models, pinpoint bottlenecks, and execute graph, kernel, and operator-level optimizations. Refine deployment pipelines to boost throughput and improve latency across these leading platforms.

AI is rapidly becoming the foundation of modern product management — transforming how we discover customer needs, define solutions, and make decisions. Just as electricity revolutionized industry, Artificial Intelligence is reshaping how products are built, validated, and evolved.

This instructor-led, live training (online or onsite) is aimed at Product Owners, Scrum Masters, and Agile Coaches who want to understand how AI can enhance product ownership and strengthen decision-making.

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

• Understand the fundamentals of Artificial Intelligence and differentiate between traditional AI and Generative AI (GenAI).
• Apply the seven preferred stances of a Product Owner (including the new Orchestrator stance) and use AI to strengthen each stance — such as Visionary, Experimenter, or Customer Representative.
• Master effective prompting and treat AI tools as intelligent collaborators with specialized skills.
• Deepen customer understanding and create AI-supported personas for hypothesis testing and discovery, while maintaining authentic customer contact.
• Develop and communicate a clear product vision using structured frameworks like the 3x3 Framework, leveraging AI to shape and visualize narratives.
• Use Generative AI tools to accelerate prototyping and hypothesis testing, such as generating mock-ups or product concepts.
• Support product decisions by using AI tools to analyze, prioritize, and evaluate features based on value, feasibility, and user impact.
• Automate or delegate routine daily tasks (emails, stakeholder management, note-taking) using AI to focus on strategic and creative work.
• Lead discussions on AI ethics, bias, and data security, ensuring responsible and sustainable AI adoption.
• Identify and design valuable AI use cases tailored to the specific product and organizational context.
• Explore and experiment with around 20 different AI tools and models — from productivity assistants and prototyping platforms to generative video, image, and coding solutions.