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

This instructor-led, live training in Romania (online or onsite) is designed for beginner to intermediate AI engineers and software developers seeking a solid foundation in AI engineering principles and practices.

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

• Grasp the core concepts and technologies underlying AI and machine learning.
• Construct basic machine learning models using TensorFlow and PyTorch.
• Utilize AI techniques to resolve practical issues in software development.
• Manage and sustain AI projects by adhering to best practices in AI engineering.
• Awareness of the ethical implications and responsibilities associated with developing AI systems.

Over this intensive two-day, hands-on session, participants will acquire the practical skills needed to integrate Generative AI tools effectively, securely, and consistently into their technical and operational routines. The program emphasizes transforming AI into a dependable daily companion for tasks such as drafting and refining documentation, organizing requirements, speeding up analysis and reporting, enhancing problem-solving capabilities, and facilitating smoother cross-functional communication. Learners will explore established prompting techniques, validation methods to minimize errors and "hallucinations," and streamlined governance protocols to safeguard confidential data and intellectual property. The course is structured to deliver instantly applicable templates, workflows, and a sustainable approach to AI-assisted work.

This guided, live training in Romania (online or onsite) is designed for AI specialists 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 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 solving real-world challenges.
• Assess the ethical implications of AI applications across various industries.

This instructor-led, live training in Romania (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 Romania (online or on-site) is designed for intermediate to advanced data scientists, engineers, and AI practitioners who aim to master the nuances of intelligent applications and apply 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.

This instructor-led live training in Romania (online or onsite) is designed for beginner to intermediate 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 Romania (online or onsite) is aimed at beginner-level to intermediate-level data scientists and software developers who wish to learn how to apply Pinecone to various AI scenarios, from semantic search to personalization.

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

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

Artificial Intelligence is steadily emerging as the cornerstone of contemporary product management, fundamentally altering how we uncover customer requirements, craft solutions, and drive decision-making. Much like electricity transformed industrial landscapes, AI is redefining the way products are designed, validated, and refined over time.

Delivered by a certified instructor, this live training—available either online or in person—is designed for Product Owners, Scrum Masters, and Agile Coaches seeking to grasp how AI can augment their product ownership responsibilities and fortify their strategic decisions.

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

• Grasp the core principles of Artificial Intelligence and distinguish between conventional AI and Generative AI (GenAI).
• Utilize the seven key stances of a Product Owner (including the recently introduced Orchestrator stance) and leverage AI to reinforce each role—whether as a Visionary, Experimenter, or Customer Representative.
• Become proficient in effective prompting techniques, viewing AI tools as skilled intelligent partners rather than just utilities.
• Enhance customer insights by developing AI-assisted personas for hypothesis testing and discovery, all while preserving genuine human connection with users.
• Formulate and articulate a distinct product vision using established structures such as the 3x3 Framework, employing AI to refine and visualize these narratives.
• Hasten prototyping and hypothesis validation with Generative AI tools, capable of producing mock-ups or novel product concepts.
• Inform product decisions by employing AI to analyze, prioritize, and assess features based on value, technical feasibility, and user impact.
• Streamline or outsource routine daily operations—such as email management, stakeholder coordination, and note-taking—via AI, allowing focus to shift toward strategic and creative initiatives.
• Facilitate dialogues concerning AI ethics, bias, and data security, guaranteeing a responsible and sustainable integration of AI technologies.
• Pinpoint and architect impactful AI use cases customized to your specific product and organizational environment.
• Investigate and test approximately 20 diverse AI tools and models—ranging from productivity assistants and prototyping platforms to generative video, image, and coding applications.

This instructor-led, live training in Romania (online or onsite) is aimed at beginner-level software developers and database administrators who wish to learn the basics of vector databases, including their structure, operation, and use cases.

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

• Grasp the concept and purpose of vector databases.
• Distinguish between vector and traditional databases.
• Learn fundamental techniques for creating and managing vector data.
• Execute simple similarity searches.
• Understand the role of vector databases in AI applications.

This instructor-led, live training in Romania (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.