An AI Assistant on Your Company Knowledge, Without Code Training Course

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

By the conclusion 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.

Spanning two days, this practical workshop enables participants to develop the hands-on skills necessary to deploy Generative AI tools effectively, securely, and consistently across technical and operational environments. The focus is on transforming AI into a trusted daily companion for enhancing documentation, organizing requirements, speeding up analysis and reporting, aiding problem-solving, and improving cross-functional dialogue. Participants will acquire knowledge of proven prompting methodologies, validation techniques to mitigate errors and 'hallucinations,' and lightweight governance measures to secure confidential information and intellectual property. The course is crafted to deliver immediately actionable templates, efficient workflows, and a replicable approach to AI-assisted tasks.

This instructor-led, live training in Greece (online or onsite) is designed for AI professionals and software developers at intermediate to advanced levels who want to create smart applications using AI and ML.

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

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

This instructor-led, live training in is aimed at anyone who wants to ensure their organization is compliant, minimizes risks, and empowers your workforce to leverage AI safely and ethically.

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

• Understand how AI systems function and their potential applications.
• Identify risks and limitations associated with AI systems.
• Adhere to relevant legal and ethical requirements.

This instructor-led, live training in Greece (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 Greece (online or onsite) is designed for intermediate to advanced-level data scientists, engineers, and AI professionals seeking to master the nuances of intelligent applications and apply them to solve intricate, real-world challenges.

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

• Implement and analyze deep learning architectures.
• Deploy machine learning models at scale within distributed computing environments.
• Design and execute reinforcement learning models to support decision-making.
• Develop advanced NLP systems for robust language understanding.
• Apply computer vision techniques for image and video analysis.
• Navigate ethical considerations during the development and deployment of AI systems.

This instructor-led, live training in Greece (online or on-site) is designed for beginner to intermediate-level data scientists and software developers who want to learn about Milvus and its practical applications in various AI scenarios.

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

• Understand the architecture and features of Milvus.
• Implement vector databases in different AI applications.
• Perform similarity searches with high accuracy and speed.
• Apply Milvus to real-world AI challenges.

This instructor-led, live training in Greece (online or onsite) targets beginner- to intermediate-level data scientists and software developers who aim to learn how to apply Pinecone to diverse AI scenarios, from semantic search to personalization.

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

• Grasp the architecture and capabilities of Pinecone.
• Deploy vector databases in various AI applications.
• Conduct similarity searches with high precision and velocity.
• Utilize Pinecone to solve real-world AI challenges.

Artificial Intelligence is rapidly becoming the cornerstone of modern product management, transforming how we identify customer needs, define solutions, and make decisions. Much like electricity revolutionized industry, AI is reshaping how products are built, 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.

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

• Understand 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 Orchestrator stance) and leverage AI to strengthen each, such as Visionary, Experimenter, or Customer Representative.
• Master effective prompting to treat 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, including 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.

This instructor-led, live training in Greece (online or onsite) is designed for beginner-level software developers and database administrators who wish to learn the fundamentals of vector databases, covering their structure, operation, and practical applications.

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

• Grasp the concept and purpose of vector databases.
• Distinguish between vector databases and traditional database systems.
• Acquire foundational techniques for creating and managing vector data.
• Execute basic similarity searches.
• Understand the critical role vector databases play in AI applications.

This instructor-led, live training in Greece (online or onsite) is aimed at intermediate-level to advanced-level data scientists and machine learning engineers who wish to master the use of vector databases for scalable, high-performance AI applications.

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

• Understand the principles of vector databases.
• Learn techniques for creating and managing vector embeddings.
• Explore indexing strategies for high-dimensional data.
• Develop skills for performing efficient similarity searches.
• Apply vector database knowledge to machine learning projects.