AI Engineering Training in Gaia

This instructor-led, live training in Gaia (online or onsite) is tailored for intermediate to advanced AI professionals and software developers who wish to build 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.
• Analyse and visualize data to guide the development of AI/ML models.
• Effectively build, train, and deploy AI/ML models.
• Develop intelligent applications capable of addressing real-world problems.
• Assess the ethical implications of AI applications across various industries.

This instructor-led, live training in Gaia (online or on-site) is designed for intermediate to advanced data scientists, engineers, and AI practitioners aiming to master the nuances of intelligent applications and utilize them to solve intricate, real-world challenges.

Upon completing this training, participants will be capable of:

• Implementing and analyzing deep learning architectures.
• Applying machine learning at scale within distributed computing environments.
• Designing and executing reinforcement learning models for decision-making.
• Developing sophisticated natural language processing (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.

This guided, live training in Gaia (online or in-person) is tailored for beginner to intermediate AI engineers and software developers aiming to build a foundational understanding of AI engineering principles and practices.

By the conclusion of this training, participants will be capable of:

• Understanding the core concepts and technologies behind AI and machine learning.
• Implementing basic machine learning models using TensorFlow and PyTorch.
• Applying AI techniques to solve practical problems in software development.
• Managing and maintaining AI projects using best practices in AI engineering.
• Recognizing the ethical implications and responsibilities involved in developing AI systems.

This instructor-led, live training in Gaia (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 days, this hands-on initiative empowers participants with the practical competencies needed to leverage Generative AI tools effectively, securely, and consistently within technical and operational contexts. The programme centres on transforming AI into a dependable daily aid for drafting and enhancing documentation, organizing requirements, expediting analysis and reporting, facilitating problem-solving, and optimising cross-functional communication. Learners will acquire established prompting patterns, validation methods to mitigate errors and 'hallucinations,' and streamlined governance protocols to safeguard confidential data and intellectual property. The course is structured to yield immediately applicable templates, workflows, and a sustainable approach to AI-assisted productivity.

Artificial Intelligence is swiftly becoming the backbone of contemporary product management, fundamentally altering how we uncover customer needs, design solutions, and drive strategic decisions. Much like the advent of electricity transformed industrial capabilities, AI is redefining the lifecycle of product creation, validation, and evolution.

This live, instructor-led training—available both online and on-site—is specifically designed for Product Owners, Scrum Masters, and Agile Coaches seeking to leverage AI to enhance product ownership and reinforce decision-making processes.

Upon completing this program, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and distinguish between conventional AI and Generative AI (GenAI).
• Implement the seven key stances of a Product Owner, including the emerging Orchestrator role, while utilizing AI to bolster each stance—whether acting as a Visionary, Experimenter, or Customer Representative.
• Develop proficiency in effective prompting, treating AI tools as skilled, intelligent collaborators rather than mere utilities.
• Deepen insights into customer behaviour by creating AI-assisted personas for discovery and hypothesis testing, all while preserving genuine, direct customer engagement.
• Craft and articulate a clear product vision using structured methodologies such as the 3x3 Framework, using AI to refine and visualise strategic narratives.
• Accelerate prototyping and hypothesis testing by deploying Generative AI tools to generate mock-ups and conceptual product ideas.
• Inform product decisions by leveraging AI to analyse, prioritise, and assess features based on value, feasibility, and user impact.
• Delegate or automate routine operational tasks—such as email management, stakeholder coordination, and note-taking—allowing more time to focus on strategic and creative initiatives.
• Facilitate informed discussions on AI ethics, bias, and data security, ensuring that AI adoption remains responsible and sustainable.
• Identify and craft high-value AI use cases that are precisely aligned with specific product requirements and organisational contexts.
• Experiment with approximately 20 distinct AI tools and models, ranging from productivity assistants and prototyping platforms to generative video, image, and coding solutions.

This live, instructor-led training on Gaia is tailored for teams looking to extract answers from their own documents and guidelines.

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

• Prepare documents for AI processing
• Create a knowledge assistant via Claude Projects, custom GPTs, or Langdock
• Obtain answers with cited sources
• Keep the knowledge base current