AI Agents Training in Bratislava

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level AI engineers, robotics developers, and automation specialists who wish to leverage DeepSeek for building intelligent AI agents and autonomous systems.

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

• Understand the architecture and capabilities of DeepSeek AI models.
• Integrate DeepSeek into AI agents for decision-making and automation.
• Apply reinforcement learning techniques for training autonomous systems.
• Deploy AI-driven autonomous agents in real-world environments.

Autonomous AI agents are increasingly being incorporated into decision-making processes in sectors such as defense, healthcare, finance, and infrastructure. As these systems gain more independence and autonomy, there is an urgent need for robust ethical frameworks, governance mechanisms, and regulatory oversight to guide their design and deployment.

This instructor-led, live training (available online or on-site) is designed for advanced-level professionals who wish to delve into the ethical, societal, and regulatory implications of deploying autonomous AI agents in real-world settings.

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

• Analyze the ethical risks and moral dilemmas associated with autonomous AI agents.
• Evaluate governance frameworks and regulatory models pertinent to high-stakes AI deployment.
• Assess accountability, explainability, and transparency mechanisms in autonomous systems.
• Develop strategies for aligning AI agent behavior with legal, ethical, and societal values.

Format of the Course

• Interactive lecture and discussion.
• Case studies and role-playing simulations.
• Hands-on analysis of governance models and ethical frameworks.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

AI-powered automation merges the adaptability of no-code platforms with the intelligence of large language models and autonomous agents to develop scalable, intelligent systems.

This instructor-led, live training (available online or on-site) is designed for intermediate-level professionals who want to design, build, and optimize automation pipelines enhanced with AI decision-making, orchestration, and self-execution capabilities.

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

• Design no-code automation workflows that are enriched by AI interpretation and responses.
• Utilize prompt chaining, webhook triggers, and APIs to construct scalable logic flows.
• Create intelligent applications that connect services and interpret data autonomously.
• Understand, design, and deploy AI agents capable of goal-oriented action planning and execution.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level AI developers, security specialists, and compliance officers who wish to design and implement secure AI agents while addressing ethical concerns and robustness.

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

• Understand the security risks and ethical challenges in AI agent development.
• Implement security-first design principles for AI models.
• Apply adversarial robustness techniques to prevent attacks on AI agents.
• Ensure compliance with ethical AI guidelines and regulatory standards.

Edge & Lightweight Agents is a practical course designed to help participants deploy AI workloads on devices with limited resources. The course covers building, optimizing, and managing lightweight agents that can perform local reasoning and inference, enhancing speed, privacy, and reliability in distributed environments. It emphasizes performance tuning, low-latency design, and the integration of hardware and software.

This live training, led by an instructor and available both online and onsite, is targeted at intermediate-level professionals who want to implement and optimize on-device agentic systems using Python and edge AI frameworks.

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

• Understand the architecture and challenges associated with running agentic AI on edge devices.
• Design lightweight agent loops that are suitable for resource-constrained environments.
• Implement local inference using TensorFlow Lite, PyTorch Mobile, and ONNX.
• Integrate agents with sensors, actuators, and IoT platforms.
• Optimize performance, energy consumption, and latency for real-time operations.

Format of the Course

• Interactive lectures and practical demonstrations.
• Hands-on development in local or emulated environments.
• Project-based learning with guided implementation exercises.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level to advanced-level AI developers, researchers, and multimedia engineers who wish to build AI agents capable of understanding and generating multi-modal content.

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

• Develop AI agents that process and integrate text, image, and speech data.
• Implement multi-modal models such as GPT-4 Vision and Whisper ASR.
• Optimize multi-modal AI pipelines for efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in Bratislava (online or onsite) is aimed at beginner-level to intermediate-level developers and designers who wish to understand and build AI-powered personal assistants for various use cases.

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

• Understand the core principles of AI-powered personal assistants.
• Learn the fundamentals of integrating language models with smart assistants.
• Build and customize a personal assistant using AI frameworks and tools.
• Deploy personal assistants for real-world applications in different industries.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level AI engineers, enterprise software developers, and business leaders who wish to customize and deploy LLM-based AI agents for enterprise applications.

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

• Understand the architecture and capabilities of open-source LLMs.
• Customize and fine-tune LLMs for enterprise use cases.
• Deploy AI agents using LangChain and Hugging Face.
• Integrate LLM-powered agents into business workflows.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level robotics engineers, AI researchers, and automation specialists who wish to develop AI-driven autonomous robotic systems for complex tasks and human-AI collaboration.

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

• Understand the role of AI agents in robotic decision-making and automation.
• Implement AI-driven navigation and obstacle avoidance.
• Develop human-AI collaborative robotic systems.
• Deploy AI-powered perception and control systems in robots.

This course delves into the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will gain knowledge on building agents that can communicate, collaborate, and adapt to achieve common goals in complex, dynamic environments.

This instructor-led, live training (available online or onsite) is designed for advanced-level professionals who are interested in designing and implementing multi-agent systems for intelligent automation, simulation, and decision-making applications.

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

• Grasp the architecture and principles underlying multi-agent systems.
• Develop agents with capabilities in communication, coordination, and negotiation.
• Set up distributed environments for agent interactions.
• Utilize reinforcement learning and planning techniques in multi-agent contexts.
• Simulate both cooperative and competitive behaviors among agents.
• Create hybrid workflows that integrate human input with intelligent agents.

Format of the Course

• Instructor-led lectures and live demonstrations.
• Practical exercises using open-source agent frameworks.
• A group project that simulates a multi-agent scenario.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level financial professionals, risk analysts, and AI engineers who wish to develop and deploy AI-driven solutions for financial automation and fraud detection.

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

• Understand the role of AI in financial automation and fraud detection.
• Build AI models for detecting fraudulent transactions.
• Leverage machine learning for real-time risk assessment.
• Deploy AI-powered financial monitoring systems.

This instructor-led, live training in Bratislava (online or onsite) is aimed at beginner-level to intermediate-level customer service professionals, chatbot developers, and automation teams who wish to implement AI-driven solutions for customer support and service automation.

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

• Understand the fundamentals of AI-powered customer support.
• Develop and integrate AI chatbots for handling customer queries.
• Leverage NLP and machine learning to enhance chatbot interactions.
• Deploy AI agents in real-world customer service applications.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals and AI developers who wish to implement AI-driven healthcare solutions.

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

• Understand the role of AI agents in healthcare and diagnostics.
• Develop AI models for medical image analysis and predictive diagnostics.
• Integrate AI with electronic health records (EHR) and clinical workflows.
• Ensure compliance with healthcare regulations and ethical AI practices.

This instructor-led, live training in Bratislava (online or onsite) is aimed at beginner-level to intermediate-level AI developers and UI/UX designers who wish to learn how to build, optimize, and deploy AI-powered virtual assistants.

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

• Design effective conversational AI workflows and UI/UX interfaces.
• Implement AI-driven natural language processing (NLP) models.
• Integrate AI assistants with APIs and third-party platforms.
• Deploy and maintain AI assistants for real-world applications.

Mistral AI is a powerful suite of open-source and enterprise-ready AI models designed for language, multimodal, and agentic applications.

This instructor-led, live training (available online or on-site) is targeted at intermediate to advanced professionals who aim to build, deploy, and manage AI agents using Mistral’s Medium 3, Le Chat Enterprise, and Devstral models.

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

• Comprehend the architecture and capabilities of Mistral Medium 3, Le Chat Enterprise, and Devstral.
• Design and implement AI agents utilizing Mistral models for enterprise and developer scenarios.
• Integrate coding systems, connectors, and enterprise data into agent workflows.
• Optimize performance, cost, and compliance for agents powered by Mistral.

Format of the Course

• Interactive lectures and discussions.
• Numerous exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Python is the primary language driving the development and coordination of autonomous AI agents. This course emphasizes practical implementation using modern SDKs and frameworks such as LangChain and AutoGen to build, connect, and manage agent workflows.

This instructor-led, live training (online or onsite) is designed for intermediate-level backend engineers, platform engineers, and ML engineers who want to implement and coordinate autonomous agents using Python tools and APIs.

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

• Set up and configure Python-based environments for agentic systems.
• Use popular agent SDKs like LangChain and AutoGen to create functional agents.
• Integrate tools and APIs to enhance agent capabilities.
• Orchestrate multi-agent workflows and communication patterns.
• Apply best practices for debugging, testing, and maintaining agentic codebases.

Format of the Course

• Interactive lecture and discussion.
• Hands-on programming exercises and live demonstrations.
• Practical projects building end-to-end agent workflows.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Google Antigravity is a development environment tailored for creating autonomous agents that can plan, reason, code, and act using Gemini 3’s multimodal capabilities.

This training, led by an instructor, is designed for advanced technical professionals who aim to design, build, and deploy autonomous agents using Gemini 3 and the Antigravity environment. It can be conducted online or on-site.

Upon completing this training, participants will be equipped to:

• Create autonomous workflows that leverage Gemini 3 for reasoning, planning, and execution.
• Develop agents within Antigravity that can analyze tasks, write code, and interact with various tools.
• Integrate Gemini-driven agents into enterprise systems and APIs.
• Enhance the behavior, safety, and reliability of agents in complex environments.

Format of the Course

• Expert demonstrations paired with interactive discussions.
• Hands-on practice in developing autonomous agents.
• Practical implementation using Antigravity, Gemini 3, and associated cloud tools.

Course Customization Options

• If your team needs domain-specific agent behaviors or custom integrations, please contact us to customize the program.

This course provides practical engineering techniques for designing, building, testing, and deploying autonomous systems using Python. It covers the agent loop, tool integrations, memory and state management, orchestration patterns, safety controls, and production considerations.

This instructor-led, live training (available online or on-site) is aimed at intermediate to advanced ML engineers, AI developers, and software engineers who wish to build robust, production-ready autonomous agents using Python.

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

• Design and implement the agent loop and decision-making workflows.
• Integrate external tools and APIs to enhance agent capabilities.
• Implement short-term and long-term memory architectures for agents.
• Coordinate multi-step orchestrations and ensure agent composability.
• Apply safety, access control, and observability best practices for deployed agents.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs building agents with Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level professionals who wish to master the techniques for deploying and managing AI agents in production environments.

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

• Design and implement scalable AI deployment pipelines.
• Use tools like Docker and Kubernetes to containerize and orchestrate AI agents.
• Monitor and optimize AI agents in production environments.
• Implement CI/CD workflows for AI agent deployments.
• Ensure compliance with security and data governance requirements.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level AI professionals who wish to master reinforcement learning techniques and implement them for training AI agents in solving complex problems.

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

• Understand the core principles of reinforcement learning and Markov Decision Processes (MDPs).
• Design and implement RL algorithms such as Q-Learning, SARSA, and Deep Q-Networks (DQN).
• Utilize frameworks like OpenAI Gym and RL libraries for practical applications.
• Train AI agents to solve real-world, multi-step decision-making problems.
• Address challenges such as exploration-exploitation trade-offs and convergence in RL training.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level AI developers and automation specialists who wish to integrate agentic capabilities into AI-powered applications.

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

• Understand the principles of agentic AI and autonomous decision-making.
• Implement goal-driven AI agents with self-optimization techniques.
• Integrate multi-agent collaboration for complex problem-solving.
• Enhance AI-human interaction through adaptive user experiences.
• Deploy agentic AI models in real-world applications.

Google Antigravity is an agent-first development environment designed to streamline engineering workflows through intelligent automation.

This instructor-led, live training (online or onsite) is aimed at beginner-level practitioners who wish to explore the fundamentals of Antigravity and understand how agent-driven coding environments enhance productivity.

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

• Install and configure Google Antigravity.
• Navigate and understand both the Editor View and Manager View.
• Work effectively with agents to automate simple development tasks.
• Use Antigravity to generate, refine, and manage project files.

Format of the Course

• Instructor explanations supported by real-time demonstrations.
• Guided exercises focused on hands-on use of agents.
• Practical exploration of core Antigravity features in a controlled lab environment.

Course Customization Options

• If you require a tailored version of this training, please contact us to arrange a customized program.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level AI professionals who wish to master the skills to design, build, and deploy MAS that solve complex, real-world problems.

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

• Understand the principles of multi-agent system architectures.
• Implement strategies for communication, coordination, and decision-making in MAS.
• Apply game theory to model agent interactions and resolve conflicts.
• Leverage frameworks like JADE to create scalable MAS solutions.
• Address challenges like scalability, trust, and emergent behavior in MAS.

Amazon Bedrock AgentCore offers the infrastructure necessary to design, orchestrate, and manage multi-agent systems. This enables effective collaboration, specialization, and advanced automation across various AI-driven entities.

This instructor-led, live training (available online or on-site) is designed for advanced practitioners who aim to design, deploy, and optimize next-generation multi-agent systems using AgentCore’s orchestration and governance capabilities.

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

• Grasp the principles and architectures underlying multi-agent systems.
• Create effective orchestration strategies for agent collaboration.
• Implement communication and negotiation protocols between agents.
• Deploy scalable, enterprise-ready multi-agent solutions using AgentCore.

Format of the Course

• Interactive lecture and discussion sessions.
• Hands-on labs focusing on AgentCore’s orchestration features.
• Case studies of enterprise multi-agent applications.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level professionals who wish to develop and optimize multi-agent systems using Agentic AI frameworks.

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

• Understand the principles of Agentic AI in multi-agent environments.
• Develop AI-driven agents that interact autonomously.
• Implement reinforcement learning for adaptive AI behavior.
• Optimize multi-agent collaboration and competition.
• Apply Agentic AI in robotics, gaming, and enterprise automation.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level business analysts, RPA developers, and AI professionals who wish to harness the power of AI agents for business process automation.

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

• Understand the role of AI agents in business process automation.
• Identify opportunities for automation in key business domains.
• Develop AI-driven solutions for customer support, finance, and supply chain workflows.
• Integrate AI agents with existing RPA and business systems.
• Evaluate and optimize AI automation strategies for efficiency.

Google Antigravity is a platform for building agents capable of interacting with web applications, browser environments, and multi-surface workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to build, automate, and test browser-based workflows using Google Antigravity.

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

• Create agents that interact with web applications in a browser surface.
• Automate end-to-end workflows across browser contexts.
• Validate and troubleshoot agent behavior in UI-driven environments.
• Implement cross-surface automation strategies using Antigravity.

Format of the Course

• Guided instruction supported by demonstrations.
• Practical, hands-on activities and scenario-based exercises.
• Implementation of agent workflows in an interactive lab environment.

Course Customization Options

• For customized training requirements, please contact us to tailor the course to your objectives.

AgentCore simplifies the process of building, enhancing, and monitoring fully managed AI agents by offering a comprehensive suite of services designed for scalable deployment.

This instructor-led, live training (available online or on-site) is tailored for practitioners ranging from beginner to intermediate levels who want to gain practical experience in creating production-ready AI agents using AgentCore.

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

• Comprehend the essential capabilities of AgentCore for AI agent development.
• Design and configure basic AI agents using managed services.
• Integrate workflows to improve agent functionality.
• Deploy and monitor AI agents in production environments.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs with AgentCore services.
• Guided exercises from conceptualizing an agent to its deployment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Mastra is a framework that offers structured tools for assessing, debugging, and ensuring the reliability of AI agents working within complex workflows.

This instructor-led, live training (available online or on-site) is designed for intermediate-level practitioners who aim to rigorously test agent behavior, enhance reliability, and establish measurable evaluation processes.

By the end of this training, participants will confidently:

• Apply debugging techniques to identify and resolve issues in agent behavior.
• Evaluate agents using structured metrics, benchmarks, and quality scores.
• Implement tooling and workflows that monitor reliability, drift, and hallucinations.
• Develop QA strategies to ensure consistent and predictable agent performance.

Format of the Course

• Interactive lectures and discussions.
• Hands-on debugging and evaluation exercises.
• Live-lab analysis of agent behaviors using observability tools.

Course Customization Options

• Customized reliability testing scenarios and industry-specific QA methods can be arranged upon request.

Vertex AI Agent Builder is a no-code/low-code platform designed for creating grounded agents that integrate generative models with retrieval-augmented generation (RAG). This allows teams to quickly develop agents capable of providing accurate and context-aware responses by leveraging enterprise data and search capabilities.

This instructor-led, live training (available online or on-site) is targeted at intermediate-level practitioners who aim to design, configure, and deploy intelligent agents using Vertex AI Agent Builder and RAG patterns.

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

• Create grounded agent workflows using Agent Builder.
• Set up RAG pipelines that incorporate search and vector stores.
• Securely integrate enterprise data sources for retrieval purposes.
• Assess and refine agent behavior through testing and performance metrics.

Format of the Course

• Interactive lectures and discussions.
• Practical labs using Vertex AI Agent Builder and RAG components.
• Project-based exercises to build and improve agents.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Mastra is a framework that facilitates deep integration between AI agents, APIs, enterprise applications, and external data systems.

This instructor-led, live training (available online or on-site) is designed for intermediate-level engineers who want to build reliable, secure, and scalable integrations between Mastra agents and the broader enterprise ecosystem.

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

• Implement API-driven integrations between Mastra agents and external services.
• Connect enterprise data systems and tools to automated agent workflows.
• Apply best practices for secure data exchange and authentication.
• Design integration layers that are scalable, maintainable, and ready for production use.

Format of the Course

• Interactive lecture and discussion.
• Hands-on integration engineering and API exercises.
• Live-lab implementation using real-world enterprise scenarios.

Course Customization Options

• Custom API scenarios, enterprise system mappings, or data-integration workshops can be arranged upon request.

AgentCore provides memory persistence, a secure code interpreter, and a browser tool that enable AI agents to deliver interactive, dynamic, and context-aware experiences.

This instructor-led, live training (online or onsite) is aimed at intermediate-level to advanced-level technical practitioners who wish to design and deploy AI agents capable of maintaining long-term context, performing on-the-fly computations, and directly interacting with web user interfaces.

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

• Implement AgentCore memory for stateful, context-aware workflows.
• Leverage the secure code interpreter for dynamic calculations and transformations.
• Integrate the browser tool for real-time data retrieval and user interface interaction.
• Design interactive agents for analytics, customer support, and research scenarios.

Format of the Course

• Interactive lecture and discussion.
• Hands-on lab exercises with AgentCore memory and tools.
• Case studies in analytics, automation, and customer support contexts.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level game developers and AI enthusiasts who wish to integrate AI agents into gaming applications effectively.

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

• Understand the role of AI agents in modern gaming.
• Develop decision-making systems using decision trees and finite state machines.
• Implement pathfinding algorithms such as A* for in-game navigation.
• Apply reinforcement learning techniques to create adaptive AI behaviors.
• Optimize AI performance for real-time gaming environments.

Large language models (LLMs) and autonomous agent frameworks like AutoGen and CrewAI are transforming the way DevOps teams automate tasks such as change tracking, test generation, and alert triage by simulating human-like collaboration and decision-making processes.

This instructor-led, live training (available online or on-site) is designed for advanced-level engineers who aim to design and implement DevOps automation workflows powered by large language models (LLMs) and multi-agent systems.

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

• Integrate LLM-based agents into CI/CD workflows to achieve smarter automation.
• Automate test generation, commit analysis, and change summaries using these agents.
• Coordinate multiple agents for alert triage, response generation, and DevOps recommendations.
• Build secure and maintainable agent-powered workflows using open-source frameworks.

Format of the Course

• Interactive lectures and discussions.
• Plenty of exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Antigravity is a framework that embodies advanced development workflows driven by intelligent agents.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced professionals who aim to verify, validate, and secure the outputs generated by AI agents within Antigravity environments.

Upon completing this training, participants will be able to:

• Evaluate the precision and safety of code artifacts produced by agents.
• Employ structured methods to verify tasks executed by agents.
• Effectively analyze browser recordings and trace agent activities.
• Implement QA and security principles to ensure the reliability of agent-driven workflows.

Format of the Course

• Guided technical briefings and discussions led by an instructor.
• Practical exercises centered on verifying actual agent workflows.
• Hands-on testing and validation in a controlled lab environment.

Course Customization Options

• Scenarios, workflows, and testing examples can be tailored upon request.

This instructor-led, live training in Bratislava (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for decision-making in complex business and technical scenarios.

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

• Understand the principles of autonomous decision-making in AI.
• Design and implement AI agents that operate with minimal human intervention.
• Integrate Agentic AI into automation workflows and business systems.
• Optimize AI-driven decision processes for efficiency and scalability.
• Ensure compliance, security, and ethical considerations in AI autonomy.

Google Antigravity is an advanced framework for experimentation with long-lived agents and emergent interactive behaviors.

This instructor-led, live training (online or onsite) is aimed at advanced-level professionals who wish to design, analyze, and optimize agents capable of retaining memories, improving through feedback, and evolving over long operational horizons.

Upon completing this course, participants will gain the skills to:

• Design long-term memory structures for agent persistence.
• Implement effective feedback loops to shape agent behavior.
• Evaluate learning trajectories and model drift.
• Integrate memory mechanisms into complex multi-agent ecosystems.

Format of the Course

• Expert-led discussion paired with technical demonstrations.
• Hands-on exploration through structured design challenges.
• Application of concepts to simulated agent environments.

Course Customization Options

• If your organization requires tailored content or case-specific examples, please contact us to customize this training.

This instructor-led, live training in Bratislava (online or onsite) is aimed at intermediate-level professionals who wish to delve deeper into the design and development of autonomous agents for practical applications.

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

• Understand the foundational concepts of autonomous agents.
• Explore real-world applications of autonomous AI agents.
• Design, train, and implement agents using reinforcement learning.
• Integrate agents into existing systems for automation and decision-making.
• Address ethical considerations and challenges in deploying autonomous agents.

AgentCore offers built-in identity management, observability, and compliance features that empower organizations to deploy AI agents responsibly in enterprise settings.

This instructor-led, live training (available online or on-site) is designed for advanced practitioners who aim to design and operate secure, auditable, and compliant AI agent systems using Amazon Bedrock AgentCore.

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

• Implement enterprise-level identity and permissioning models for agents.
• Enable observability through structured logging, metrics, and tracing mechanisms.
• Apply compliance controls to meet regulatory requirements.
• Audit agent activities and maintain secure session-level controls.

Format of the Course

• Interactive lectures and discussions.
• Hands-on labs using AWS security and monitoring tools.
• Case studies from regulated enterprise environments.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Mastra is a framework that enables sophisticated workflow automation and coordination across multiple AI agents operating within distributed systems.

This instructor-led, live training (online or onsite) is aimed at intermediate-level practitioners who wish to design, orchestrate, and operate multi-agent workflows on a large scale.

By completing this training, participants will gain the skills to:

• Design complex workflows using Mastra’s orchestration capabilities.
• Coordinate multiple agents performing parallel or dependent tasks.
• Implement monitoring and debugging tools for workflow execution.
• Optimize orchestration logic to enhance reliability, throughput, and automation efficiency.

Format of the Course

• Interactive lecture and discussion.
• Hands-on workflow design and automation exercises.
• Practical implementation in a containerized live-lab environment.

Course Customization Options

• Customized automation scenarios, enterprise integrations, or workflow patterns can be provided upon request.

AgentCore Runtime & Gateway is an AWS service designed to package, deploy, and securely expose AI agents, facilitating seamless integrations with external systems.

This instructor-led, live training (online or onsite) is tailored for intermediate-level engineering teams looking to transition from agent prototypes to production by mastering the AgentCore Runtime for deployment and the Gateway for secure connectivity and API integration.

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

• Set up AgentCore Runtime environments and package agents for deployment.
• Expose agents via Gateway with authenticated, rate-limited endpoints.
• Integrate external tools and APIs into agent workflows using stable contracts.
• Implement observability, logging, and usage monitoring for production operations.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs focusing on Runtime deployments and Gateway integrations.
• Practical exercises centered on reliability, security, and rollout.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Devstral is an open-source framework designed for building and running coding agents that can interact with codebases, developer tools, and APIs to enhance engineering productivity.

This instructor-led, live training (available both online and onsite) is aimed at intermediate to advanced ML engineers, developer-tooling teams, and SREs who want to design, implement, and optimize coding agents using Devstral.

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

• Set up and configure Devstral for developing coding agents.
• Create agentic workflows for exploring and modifying codebases.
• Integrate coding agents with developer tools and APIs.
• Implement best practices for secure and efficient agent deployment.

Format of the Course

• Interactive lecture and discussion.
• Plenty of exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training in Bratislava (online or onsite) is aimed at beginner-level professionals who wish to understand how AI agents work and build their own interactive chatbot systems.

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

• Understand the basics of AI agents and their applications.
• Explore the principles of natural language processing (NLP).
• Design a conversational flow for a chatbot.
• Develop a functional chatbot using Python and related tools.
• Deploy the chatbot to interact with real users.

Mastra is an operational framework designed to streamline the deployment, scaling, and lifecycle management of AI agents in production environments.

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced technical professionals who need to operationalize AI agents reliably and efficiently across production systems.

Upon completing this training, attendees will be equipped to:

• Deploy Mastra-based AI agents into controlled, production-grade environments.
• Scale agents horizontally and vertically using platform-native features.
• Implement observability pipelines to monitor agent behavior and performance.
• Optimize runtime configurations to minimize latency, costs, and operational risks.

Format of the Course

• Interactive lectures and discussions.
• Hands-on exercises focused on real deployment scenarios.
• Live-lab implementation using containerized and orchestrated environments.

Course Customization Options

• Customization of topics, hands-on labs, or industry-specific scenarios is available upon request.

Google Antigravity is an agent-centric development platform used to orchestrate, supervise, and coordinate AI-driven coding and automation workflows.

This instructor-led, live training (online or onsite) is aimed at intermediate-level professionals who wish to design, manage, and optimize multi-agent workflows within Google Antigravity.

Upon completion of this training, participants will gain the skills to:

• Configure agent responsibilities and orchestration pipelines within the Manager interface.
• Generate and interpret Antigravity artifacts, including task lists, plans, logs, and browser recordings.
• Implement verification strategies to ensure agent actions remain transparent and auditable.
• Optimize multi-agent collaboration for complex development and operational tasks.

Format of the Course

• Guided presentations and practical demonstrations.
• Scenario-based exercises focused on real workflow challenges.
• Hands-on experimentation within a live Antigravity workspace.

Course Customization Options

• If you require a tailored version of this course, please contact us to discuss customization options.

This instructor-led, live training in Bratislava (online or onsite) is aimed at beginner-level professionals who wish to understand and create simple AI agents for real-world applications.

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

• Understand the fundamental concepts of AI agents.
• Identify different types of AI agents and their applications.
• Design and implement basic AI agents for practical tasks.
• Explore tools and frameworks for building AI agents.

Antigravity is a development platform designed for building AI-driven applications that prioritize the use of autonomous agents.

This instructor-led, live training (available both online and on-site) is targeted at intermediate-level developers who aim to create practical applications using autonomous AI agents within the Antigravity environment.

After completing this training, participants will be well-prepared to:

• Develop applications that leverage autonomous and coordinated AI agents.
• Utilize the Antigravity IDE, editor, terminal, and browser for comprehensive development processes.
• Manage multi-agent workflows using the Agent Manager.
• Integrate agent functionalities into production-ready software systems.

Format of the Course

• A blend of detailed presentations and demonstrations.
• Extensive hands-on practice and guided exercises.
• Practical implementation work within the live Antigravity environment.

Course Customization Options

• For content tailored to your specific development stack, please contact us to arrange a customized version of this training.

Amazon Bedrock AgentCore is an enterprise-ready framework designed for building, deploying, and scaling AI agents. It includes integrated support for memory management, observability, and secure identity handling.

This instructor-led, live training (available both online and onsite) is targeted at intermediate to advanced engineers and architects who aim to design, secure, and manage agentic AI systems using AWS Bedrock AgentCore.

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

• Understand the architecture and components of AgentCore.
• Deploy and manage AI agents using Runtime and Gateway.
• Implement persistent memory and stateful interactions.
• Apply identity, observability, and compliance controls.
• Design multi-agent systems for enterprise-scale workflows.

Format of the Course

• Interactive lecture and discussion sessions.
• Hands-on AWS lab exercises with AgentCore.
• Practical exercises focusing on deployment and monitoring scenarios.

Course Customization Options

• For a customized training for this course, please contact us to arrange.

Building LLM Agent Systems with AutoGen is a practical course designed to help you develop multi-agent systems using Microsoft’s AutoGen framework for large language models (LLMs).

This instructor-led, live training (available both online and on-site) is targeted at intermediate-level AI and automation professionals who are interested in designing, implementing, and managing multi-agent systems with AutoGen using Python and LLMs.

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

• Create multi-agent architectures using the AutoGen framework.
• Define agent roles, capabilities, and coordination behaviors.
• Implement function-calling and memory handling for effective agent interactions.
• Develop and test Python-based LLM agent workflows for real-world applications.

Format of the Course

• Interactive lectures and discussions.
• Plenty of exercises and practice sessions.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

This instructor-led, live training (online or onsite) is aimed at intermediate-level software developers and engineering teams who wish to build scalable, observable AI systems using Mastra.

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

• Understand Mastra’s architecture and how it integrates with LLMs and external APIs.
• Design and implement AI agents and workflows using TypeScript.
• Use Mastra’s observability and memory tools to monitor and improve agent performance.
• Deploy production-ready AI applications leveraging Mastra’s framework features.

This 1-day workshop, designed for developers, data scientists, and AI enthusiasts, will help you understand and harness the power of agentic AI systems using AutoGen v0.4.

Through a mix of hands-on exercises and practical demonstrations, you’ll learn how to build, manage, and deploy multi-agent applications powered by Large Language Models (LLMs).

By the end of the course, you'll gain a solid foundation in AutoGen’s layered architecture, master asynchronous communication between agents, and explore real-world use cases and best practices for developing scalable and intelligent LLM-driven applications.