AI Engineering Training in Lyon

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

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

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

This instructor-led live training, conducted Lyon (online or onsite), targets intermediate to advanced data scientists, engineers, and AI practitioners seeking to master the complexities of intelligent applications and leverage them to address 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.

This instructor-led, live training in Lyon (online or onsite) is aimed at beginner-level to intermediate-level AI engineers and software developers who wish to gain a foundational understanding 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 instructor-led, live training in Lyon (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.

Spanning two intensive days, this hands-on initiative provides participants with the practical competencies needed to leverage Generative AI tools effectively, securely, and consistently within technical and operational contexts. The training aims to establish AI as a trustworthy daily partner for creating and polishing documentation, structuring requirements, speeding up analysis and reporting, aiding problem-solving efforts, and simplifying cross-functional dialogue. Attendees will master proven prompting patterns, validation techniques that minimize errors and “hallucinations,” and streamlined governance practices to ensure the protection of sensitive information and intellectual property. The program is tailored to deliver instantly applicable templates, efficient workflows, and a repeatable framework for AI-supported tasks.

Artificial Intelligence is swiftly establishing itself as the cornerstone of contemporary product management, fundamentally altering how organizations identify customer needs, craft solutions, and drive strategic decisions. Much like the industrial revolution brought about by electricity, AI is redefining the lifecycle of products—from initial construction to validation and long-term evolution.

Designed for Product Owners, Scrum Masters, and Agile Coaches, this live, instructor-led training (available online or onsite) explores how AI can amplify product ownership capabilities and reinforce evidence-based decision-making.

Upon completion, participants will be equipped to:

• Grasp the core principles of AI and distinguish between conventional AI systems and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner, including the emerging Orchestrator role, leveraging AI to enhance specific capabilities such as Visionary, Experimenter, or Customer Representative.
• Refine prompting techniques to interact with AI tools as specialized, intelligent collaborators.
• Deepen customer insights by creating AI-assisted personas for hypothesis testing and discovery, while preserving genuine customer engagement.
• Formulate and articulate a distinct product vision using structured methodologies like the 3x3 Framework, utilizing AI to refine and visualize narratives.
• Leverage Generative AI to expedite prototyping and hypothesis validation, including the generation of mock-ups and product concepts.
• Enhance product decision-making by employing AI to analyze, prioritize, and assess features based on value, feasibility, and user impact.
• Delegate or automate routine operational tasks—such as correspondence, stakeholder coordination, and note-taking—to prioritize strategic and creative endeavors.
• Facilitate discussions on AI ethics, algorithmic bias, and data security, promoting responsible and sustainable adoption.
• Identify and design high-value AI use cases aligned with specific product and organizational contexts.
• Explore and test approximately 20 diverse AI tools and models, ranging from productivity assistants and prototyping platforms to generative video, image, and coding solutions.

Tailored for teams seeking to extract answers from their internal documentation, this instructor-led live training in Lyon provides a comprehensive solution.

By the conclusion of the session, participants will be equipped to:

• Structure and prepare documents for AI consumption
• Develop a knowledge assistant utilizing Claude Projects, custom GPTs, or Langdock
• Access responses with clear source attribution
• Ensure the knowledge base remains current and relevant