AI Engineering Training in the Netherlands

This instructor-led training in the Netherlands provides an introduction to CloudMatrix for scalable AI inference. Participants will learn to deploy, optimize, and monitor models using CANN and MindSpore. Practical exercises focus on packaging, conversion, serving, and performance tuning for both real-time and batch workloads.

This instructor-led, live training in the Netherlands (online or onsite) is designed for intermediate to advanced-level AI professionals and software developers looking to construct intelligent applications using AI and ML.

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

• Grasp the advanced concepts and technologies underpinning AI and ML.
• Analyze and visualize data to guide the development of AI/ML models.
• Effectively build, train, and deploy AI/ML models.
• Develop intelligent applications capable of solving real-world problems.
• Assess the ethical implications of AI applications across various industries.

This instructor-led, live training in the Netherlands (online or onsite) is designed for intermediate-to-advanced data scientists, engineers, and AI practitioners who aim to master the complexities of intelligent applications and utilize them to resolve intricate, real-world challenges.

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

• Implement and analyze deep learning architectures.
• Apply machine learning at scale within a distributed computing environment.
• Design and execute reinforcement learning models for decision-making.
• Develop sophisticated NLP systems for language understanding.
• Utilize computer vision techniques for image and video analysis.
• Address ethical considerations in the development and deployment of AI systems.

This instructor-led live training in the Netherlands (available online or onsite) is designed for beginner to intermediate-level AI engineers and software developers aiming to establish a foundational understanding of AI engineering principles and practices.

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

• Grasp the fundamental concepts and technologies underpinning AI and machine learning.
• Develop basic machine learning models utilizing TensorFlow and PyTorch.
• Utilize AI techniques to address practical issues in software development.
• Oversee and sustain AI projects by adhering to industry best practices.
• Identify the ethical implications and responsibilities associated with developing AI systems.

This live training on the Netherlands empowers developers to program and optimize applications on Biren AI accelerators. Participants will explore the GPU architecture, configure the SDK, and translate CUDA code to Biren, with a strong focus on performance tuning and debugging techniques.

This instructor-led live training in the Netherlands (online or onsite) is designed for beginner-level IT professionals aiming to build a foundational understanding of intelligent applications and their industry 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 practical use cases and limitations of AI across different sectors.
• Navigate ethical considerations and broader societal implications of AI technology.

This intensive two-day practical program provides participants with the practical abilities needed to utilize Generative AI tools effectively, securely, and consistently in technical and operational settings. The training centers on converting AI into a trustworthy everyday assistant for creating and enhancing documentation, organizing requirements, expediting analysis and reporting, facilitating problem-solving, and improving cross-departmental communication. Participants will study established prompting patterns and verification techniques to mitigate errors and 'hallucinations,' alongside lightweight governance practices that protect sensitive information and intellectual property. The course is structured to yield immediately usable templates, workflows, and a repeatable methodology for AI-supported tasks.

Artificial Intelligence is swiftly emerging as the cornerstone of contemporary product management, fundamentally altering how we identify customer needs, define solutions, and make informed decisions. Much like electricity once revolutionized industrial practices, AI is now reshaping the way products are developed, validated, and iterated upon.

This instructor-led, live training course (available online or onsite) is designed for Product Owners, Scrum Masters, and Agile Coaches seeking to comprehend how AI can augment product ownership and fortify decision-making processes.

Upon completing this training, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and distinguish between traditional AI and Generative AI (GenAI).
• Apply the seven key stances of a Product Owner (including the new Orchestrator role) and leverage AI to enhance each stance, such as Visionary, Experimenter, or Customer Representative.
• Master the art of effective prompting, treating AI tools as intelligent collaborators with specialized capabilities.
• Deepen customer insights by creating AI-assisted personas for hypothesis testing and discovery, while preserving genuine customer interaction.
• Develop and articulate a clear product vision using structured frameworks like the 3x3 Framework, utilizing AI to craft and visualize narratives.
• Utilize Generative AI tools to expedite prototyping and hypothesis testing, including the generation of mock-ups and product concepts.
• Support product decisions by employing AI tools to analyze, prioritize, and evaluate features based on value, feasibility, and user impact.
• Automate or delegate routine daily tasks (such as emails, stakeholder management, and note-taking) using AI, allowing focus on strategic and creative endeavors.
• Lead discussions on AI ethics, bias, and data security to ensure responsible and sustainable AI adoption.
• Identify and design valuable AI use cases tailored to specific product and organizational contexts.
• Explore and experiment with approximately 20 different AI tools and models, ranging from productivity assistants and prototyping platforms to generative video, image, and coding solutions.