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

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

Upon completing this training, participants will be capable of:

• Gaining insight into the core concepts and technologies driving AI and machine learning.
• Developing basic machine learning models using TensorFlow and PyTorch.
• Applying AI techniques to resolve practical software development challenges.
• Managing and maintaining AI projects through established best practices in AI engineering.
• Awareness of the ethical implications and responsibilities associated with developing AI systems.

Over the course of two days, this hands-on workshop empowers participants with the practical abilities needed to leverage Generative AI tools effectively, securely, and consistently within their technical and operational roles. The training is centered on establishing AI as a dependable daily aid for creating and refining documentation, organizing requirements, speeding up analysis and reporting, aiding in problem resolution, and facilitating smoother cross-functional communication. Learners will acquire established prompting strategies, verification methods to minimize errors and "hallucinations," and streamlined governance protocols to safeguard confidential data and intellectual property. The course is structured to deliver immediately applicable templates, workflows, and a scalable methodology for AI-assisted tasks.

This instructor-led, live training in Czech Republic (online or onsite) targets intermediate to advanced AI professionals and software developers who aim to construct smart applications using AI and ML.

Upon completing 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 solving real-world challenges.
• Assess the ethical implications of AI applications across various industries.

This instructor-led, live training in Czech Republic (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 Czech Republic (online or onsite) is aimed at intermediate-level to advanced-level data scientists, engineers, and AI practitioners who wish to master the intricacies of intelligent applications and leverage 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 Czech Republic (online or onsite) is aimed at beginner-level to intermediate-level 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 instructor-led, live training in Czech Republic, offered online or onsite, is designed for data scientists and software developers with beginner to intermediate proficiency. It focuses on learning how to deploy Pinecone across a variety of AI scenarios, from semantic search to personalization strategies.

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

• Comprehending the architecture and features of Pinecone.
• Implementing vector databases within different AI applications.
• Conducting similarity searches characterized by high accuracy and speed.
• Applying Pinecone to solve real-world AI challenges.

Artificial Intelligence is swiftly establishing itself as the cornerstone of contemporary product management, fundamentally altering the way we uncover customer requirements, craft solutions, and drive decision-making processes. Much like electricity transformed industrial capabilities, AI is redefining the lifecycle of products—from their creation and validation to their continuous evolution.

Designed for Product Owners, Scrum Masters, and Agile Coaches, this instructor-led live training (available online or on-site) focuses on harnessing the power of AI to elevate product ownership and reinforce strategic decision-making.

Upon completion, participants will be equipped to:

• Grasp the core principles of Artificial Intelligence and clearly distinguish between conventional AI systems and Generative AI (GenAI).
• Leverage AI to enhance the seven key stances of a Product Owner—including the emerging Orchestrator role—such as acting as a Visionary, Experimenter, or Customer Representative.
• Develop proficiency in effective prompting techniques, viewing AI tools as capable collaborators with distinct specialized capabilities.
• Deepen customer insights by generating AI-assisted personas for hypothesis testing and discovery, ensuring that authentic engagement with end-users remains a priority.
• Formulate and articulate a coherent product vision using structured methodologies like the 3x3 Framework, while utilizing AI to refine and visualize key narratives.
• Accelerate the prototyping and hypothesis testing phases by employing Generative AI tools to produce mock-ups and conceptual product models.
• Inform product decisions by using AI to analyze, prioritize, and assess features based on criteria such as value, technical feasibility, and user impact.
• Optimize daily workflows by automating or delegating routine tasks—such as email management, stakeholder communication, and meeting notes—to AI, thereby freeing up time for strategic and creative initiatives.
• Facilitate informed discussions on AI ethics, algorithmic bias, and data security to guarantee responsible and sustainable implementation.
• Identify and architect high-value AI use cases that align with specific product goals and organizational contexts.
• Explore and experiment with approximately 20 distinct AI tools and models, ranging from productivity assistants and prototyping platforms to generative solutions for video, image, and code.

This instructor-led, live training in Czech Republic (online or on-site) 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:

• 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 session in Czech Republic (online or on-site) is designed for intermediate to advanced data scientists and machine learning engineers who aim to master the utilization of vector databases for scalable, high-performance AI applications.

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

• Comprehend the fundamental principles of vector databases.
• Acquire techniques for generating and managing vector embeddings.
• Examine indexing strategies tailored for high-dimensional data.
• Develop proficiency in executing efficient similarity searches.
• Apply vector database expertise to real-world machine learning projects.