AI Enablement Training for Engineers Training Course

This instructor-led course on Turkey explores CloudMatrix for scalable AI inference. It covers deploying, refining, and monitoring models via CANN and MindSpore. Practical exercises address packaging, conversion, serving, and performance tuning for both real-time and batch workloads.

This instructor-led, live training in Turkey (online or on-site) is designed for beginner to intermediate-level AI engineers and software developers who aim to establish a foundational understanding of AI engineering principles and practices.

By the end of this course, 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 Turkey empowers developers with the expertise to program and optimize applications on Biren AI accelerators. Participants will explore GPU architecture, configure the SDK, and adapt CUDA code for Biren platforms. The curriculum emphasizes performance tuning and debugging methodologies.

This instructor-led, live training in Turkey (online or onsite) is designed for intermediate to advanced-level AI professionals and software developers aiming to create smart solutions using AI and ML.

Upon completing this training, participants will be capable of:

• Grasping the advanced concepts and technologies underlying AI and ML.
• Analyzing and visualizing data to guide AI/ML model development.
• Effectively building, training, and deploying AI/ML models.
• Creating smart solutions capable of addressing real-world challenges.
• Assessing the ethical implications of AI applications across various industries.

This instructor-led, live training in Turkey (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 Turkey (online or onsite) targets data scientists, engineers, and AI practitioners at intermediate to advanced levels who wish to master the intricacies of intelligent applications and leverage them to solve complex, 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 quickly establishing itself as the cornerstone of contemporary product management — revolutionizing the way we uncover customer needs, define solutions, and make critical decisions. Just as electricity transformed industry, AI is reshaping how products are constructed, validated, and evolved.

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

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

• Grasp the fundamentals of Artificial Intelligence and distinguish between traditional AI and Generative AI (GenAI).
• Apply the seven preferred stances of a Product Owner (including the new Orchestrator stance) and utilize AI to reinforce each stance — such as Visionary, Experimenter, or Customer Representative.
• Master effective prompting techniques and view 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.