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

This instructor-led, live training in Slovakia (online or onsite) targets beginner to intermediate-level AI engineers and software developers who wish to build 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 intensive two-day workshop provides a practical foundation for leveraging Generative AI tools with precision, security, and consistency in technical and operational contexts. The curriculum is centered on establishing AI as a dependable daily partner for enhancing documentation, organizing requirements, expediting analysis and reporting, facilitating problem resolution, and optimizing cross-functional communication. Learners will master established prompting strategies, implement validation methods to minimize inaccuracies and hallucinations, and apply streamlined governance protocols to safeguard sensitive data and intellectual property. Upon completion, participants will possess ready-to-implement templates, optimized workflows, and a sustainable methodology for integrating AI-assisted tasks into their routine operations.

This instructor-led, live training in Slovakia (online or on-site) is designed for intermediate to advanced AI professionals and software developers who aim to create smart 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.
• Analyze and visualize data to guide the development of AI/ML models.
• Construct, train, and deploy AI/ML models efficiently.
• Develop smart applications capable of addressing real-world challenges.
• Assess the ethical implications of AI applications across various industries.

This instructor-led live training in Slovakia (online or onsite) is tailored for beginner-level IT professionals who wish to establish a foundational understanding of intelligent applications and their integration into 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 Slovakia (online or onsite) is designed for intermediate to advanced data scientists, engineers, and AI practitioners who aim to master the complexities of intelligent applications and utilize them to resolve 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 Slovakia (available online or on-site) is designed for beginner to intermediate data scientists and software developers who wish 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 live, instructor-led course in Slovakia (delivered online or onsite) is tailored for data scientists and software developers at beginner to intermediate levels. It provides insights into applying Pinecone to various AI use cases, spanning from semantic search to personalized experiences.

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

• Understand the core architecture and capabilities of Pinecone.
• Deploy vector databases across different AI applications.
• Conduct similarity searches with enhanced accuracy and speed.
• Apply Pinecone to solve real-world AI problems.

Artificial Intelligence is swiftly emerging as the cornerstone of contemporary product management, fundamentally altering how organizations identify customer needs, formulate solutions, and drive decision-making. Much like the industrial revolution brought about by electricity, AI is redefining the processes by which products are conceived, validated, and iterated upon.

Designed for Product Owners, Scrum Masters, and Agile Coaches, this live, instructor-led training—available both online and on-site—equips participants with the insights needed to harness AI for enhanced product ownership and more robust decision-making capabilities.

Upon completion of this program, attendees 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, and leverage AI to reinforce each perspective, such as Visionary, Experimenter, or Customer Representative.
• Achieve proficiency in effective prompting strategies, viewing AI tools not merely as utilities but as specialized, intelligent collaborators.
• Enhance customer insight by developing AI-assisted personas for discovery and hypothesis testing, while preserving genuine engagement with end users.
• Craft and articulate a compelling product vision utilizing structured methodologies like the 3x3 Framework, using AI to refine and visualize strategic narratives.
• Utilize Generative AI capabilities to expedite prototyping and hypothesis validation, including the creation of mock-ups and initial product concepts.
• Inform product strategy by employing AI to analyze, prioritize, and assess features through the lenses of business value, technical feasibility, and user impact.
• Streamline routine administrative duties, such as email management, stakeholder coordination, and note-taking, allowing for a greater focus on strategic and creative endeavors.
• Facilitate informed discourse on AI ethics, bias mitigation, and data security, promoting a responsible and sustainable approach to AI adoption.
• Identify and architect high-value AI use cases that are specifically aligned with the product’s goals and the broader organizational environment.
• Gain hands-on experience with approximately 20 diverse AI tools and models, ranging from productivity boosters and design platforms to generative solutions for video, imagery, and code.

This instructor-led live training in Slovakia (available online or onsite) targets beginner-level software developers and database administrators who wish to learn the fundamentals of vector databases, including their structure, functionality, and use cases.

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

• Understand the concept and purpose of vector databases.
• Recognize the differences between vector and traditional databases.
• Learn basic techniques for creating and managing vector data.
• Perform simple similarity searches.
• Appreciate the role of vector databases in AI applications.

This instructor-led, live training in Slovakia (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.