AI Enablement Training for Engineers Training Course

This instructor-led session on Norway presents CloudMatrix for scalable AI inference. Master the deployment, optimization, and monitoring of models utilizing CANN and MindSpore. Practical tasks address packaging, conversion, serving, and performance refinement for both real-time and batch workloads.

This instructor-led, live training in Norway (online or on-site) targets beginner to intermediate AI engineers and software developers who aim to acquire a foundational understanding of AI engineering principles and practices.

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

• Comprehend the fundamental concepts and technologies underpinning AI and machine learning.
• Develop basic machine learning models using TensorFlow and PyTorch.
• Utilize AI techniques to resolve 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 in Norway empowers developers with the expertise to program and optimize applications on Biren AI accelerators. Participants will explore the GPU architecture, configure the SDK, and translate CUDA code to Biren. The course emphasizes performance tuning and debugging methodologies.

This instructor-led live training in Norway (online or onsite) is designed for intermediate to advanced-level AI professionals and software developers who aim to build intelligent applications using AI and ML.

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

• Comprehend the advanced concepts and technologies behind AI and ML.
• Analyze and visualize data to inform the development of AI/ML models.
• Build, train, and deploy AI/ML models effectively.
• Create intelligent applications capable of solving real-world problems.
• Evaluate the ethical implications of AI applications across various industries.

This instructor-led, live training in Norway (online or on-site) is aimed at beginner-level IT professionals who wish to gain a foundational understanding of intelligent applications and how they can be applied in various industries.

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

• Understand the history, principles, and impact of artificial intelligence.
• Identify and apply different machine learning algorithms.
• Manage and analyze data effectively for AI applications.
• Recognize the practical applications and limitations of AI in different sectors.
• Discuss the ethical considerations and societal implications of AI technology.

This instructor-led, live training in Norway (online or onsite) is designed for data scientists, engineers, and AI practitioners at an intermediate to advanced level who aim to master the complexities of intelligent applications and apply them to solve challenging, real-world problems.

Upon completion of this training, participants will be capable of:

• Implementing and analyzing deep learning architectures.
• Applying machine learning at scale within a distributed computing environment.
• Designing and executing reinforcement learning models for decision-making.
• Developing advanced NLP systems for language understanding.
• Utilizing computer vision techniques for image and video analysis.
• Addressing ethical considerations in the development and deployment of AI systems.

Artificial Intelligence is swiftly emerging as the bedrock of contemporary product management, revolutionizing our approach to uncovering customer needs, defining solutions, and making critical decisions. Much like the industrial shift brought by electricity, AI is fundamentally altering how products are constructed, validated, and evolved.

This live, instructor-led training, available either online or onsite, targets Product Owners, Scrum Masters, and Agile Coaches seeking to grasp how AI can augment product ownership and fortify decision-making processes.

Upon completing this training, participants will be equipped to:

• Comprehend the core principles of Artificial Intelligence and distinguish between conventional AI and Generative AI (GenAI).
• Implement the seven recommended stances of a Product Owner (including the newly introduced Orchestrator stance), utilizing AI to reinforce each role—such as Visionary, Experimenter, or Customer Representative.
• Master the art of effective prompting and regard AI tools as intelligent collaborators possessing specialized capabilities.
• Enhance customer insights by creating AI-assisted personas for hypothesis testing and discovery, all while preserving genuine customer interactions.
• Formulate and articulate a distinct product vision through structured frameworks like the 3x3 Framework, using AI to craft and visualize compelling narratives.
• Leverage Generative AI tools to expedite prototyping and hypothesis testing, for instance, by generating mock-ups or initial product concepts.
• Inform product decisions by employing AI tools to analyze, prioritize, and assess features based on value, feasibility, and user impact.
• Automate or delegate routine daily responsibilities (such as emails, stakeholder management, and note-taking) using AI, thereby freeing up time for strategic and creative endeavors.
• Facilitate discussions regarding AI ethics, bias, and data security to ensure responsible and sustainable AI adoption.
• Identify and design high-value AI use cases that are tailored to specific product and organizational contexts.
• Explore and experiment with approximately 20 distinct AI tools and models—ranging from productivity assistants and prototyping platforms to generative video, image, and coding solutions.