AI Enablement Training for Engineers Training Course

This instructor-led session on Nigeria introduces CloudMatrix for scalable AI inference. Participants will learn to deploy, optimize, and monitor models using CANN and MindSpore. The hands-on activities cover packaging, conversion, serving, and performance tuning for both real-time and batch workloads.

This instructor-led live training in Nigeria (online or onsite) is designed for beginner to intermediate AI engineers and software developers seeking a foundational grasp of AI engineering principles and practices.

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

• Understand the core concepts and technologies behind AI and machine learning.
• Implement basic machine learning models using TensorFlow and PyTorch.
• Apply AI techniques to solve practical problems in software development.
• Manage and maintain AI projects using best practices in AI engineering.
• Recognize the ethical implications and responsibilities involved in developing AI systems.

This live training in Nigeria empowers developers with the expertise to program and refine applications on Biren AI accelerators. Learners will explore GPU architecture, configure the SDK, and convert CUDA code for Biren, with a strong emphasis on performance tuning and debugging methodologies.

This live, instructor-led training in Nigeria (online or on-site) is designed for AI professionals and software developers at intermediate to advanced levels who wish to build smart applications using AI and ML.

Upon completing this training, participants will be equipped to:

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

This instructor-led, live training in Nigeria (online or onsite) 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 Nigeria (online or onsite) is tailored for data scientists, engineers, and AI practitioners at intermediate to advanced levels who wish to master the complexities of intelligent applications and leverage them to solve intricate, real-world problems.

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

• Implement and analyze deep learning architectures.
• Apply machine learning at scale in 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.

Artificial Intelligence is swiftly becoming the cornerstone of contemporary product management, fundamentally altering the way we uncover customer requirements, design solutions, and make critical decisions. Much like electricity transformed industrial processes, AI is redefining the creation, validation, and evolution of products.

This instructor-led, live training session (available online or onsite) is designed for Product Owners, Scrum Masters, and Agile Coaches seeking to grasp how AI can elevate product ownership and bolster decision-making capabilities.

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

• Comprehend the core principles of Artificial Intelligence and distinguish between traditional AI and Generative AI (GenAI).
• Implement the seven preferred stances of a Product Owner, including the newly introduced Orchestrator stance, and utilize AI to reinforce each stance—such as Visionary, Experimenter, or Customer Representative.
• Master the art of effective prompting and regard AI tools as intelligent collaborators possessing specialized skills.
• Enhance customer insight and develop AI-assisted personas for hypothesis testing and discovery, while preserving genuine customer engagement.
• Articulate and convey a distinct product vision using structured frameworks like the 3x3 Framework, leveraging AI to craft and visualize narratives.
• Utilize Generative AI tools to expedite prototyping and hypothesis testing, for instance, by generating mock-ups or 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 tasks (emails, stakeholder management, note-taking) using AI to dedicate more time to strategic and creative endeavors.
• Facilitate discussions on AI ethics, bias, and data security, ensuring responsible and sustainable AI adoption.
• Identify and design valuable AI use cases customised to the specific product and organisational context.
• 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.