Agentic AI Training in Lisbon

Generative AI and Agentic AI represent two influential paradigms propelling the next generation of automation and intelligence. While one prioritizes content creation, the other focuses on autonomous, goal-oriented behaviour.

This instructor-led live training, available both online and on-site, is designed for intermediate-level AI specialists and technical professionals eager to learn how to build, assess, and integrate generative and agentic AI solutions into practical applications.

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

• Comprehend the architecture and capabilities of generative AI systems.
• Investigate the emergence of autonomous AI agents and their extension of Large Language Models (LLMs).
• Employ prompt engineering and tool integrations for practical deployments.
• Evaluate models, tools, and techniques to ensure responsible deployment.

Course Format

• Interactive lectures and discussions.
• Practical application of generative and agentic AI tools within real-world contexts.
• Guided exercises centred on content generation and autonomous workflows.

Course Customisation Options

• For personalised training tailored to this course, please contact us to arrange.

Agentic AI represents a new generation of systems capable of making autonomous decisions, executing tasks, and orchestrating workflows.

This instructor-led live training, available both online and onsite, is designed for intermediate-level professionals keen on understanding how agentic AI will transform organizational workflows, talent strategies, and job design.

Upon completing the course, participants will be able to:

• Evaluate the capabilities and limitations of agentic AI in enterprise settings.
• Identify opportunities for task automation, augmentation, and redesign.
• Assess workforce implications and develop responsible adoption strategies.
• Plan governance frameworks for safe, transparent, and compliant AI deployment.

Format of the Course

• Interactive lecture and discussion.
• Practical exercises and scenario-based analysis.
• Hands-on exploration of agentic workflows in a guided environment.

Course Customization Options

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

The Practical Agentic AI Bootcamp is a rigorous, project-centric course designed to equip participants with hands-on experience in designing, building, and deploying autonomous AI agents using Python. Across five increasingly complex projects, learners will explore agentic design patterns, prompt workflows, API orchestration, and real-world integration scenarios.

This instructor-led, live training (available online or onsite) targets intermediate-level professionals eager to accelerate their transition from theory to implementation by creating functional prototypes of agentic AI applications.

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

• Grasp agentic AI architectures and core design principles.
• Develop, test, and deploy multiple agent-based applications in Python.
• Integrate agents with external tools, APIs, and databases.
• Optimize prompts and workflows for enhanced performance and reliability.
• Apply best practices for monitoring, versioning, and scaling agent systems.

Course Format

• Interactive lectures coupled with guided coding sessions.
• Hands-on project development and debugging exercises.
• Live demonstration of end-to-end agent deployment.

Course Customization Options

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

Edge & Lightweight Agents is a hands-on course designed for deploying agentic AI workloads on resource-constrained devices. Participants acquire the skills to build, optimize, and manage lightweight agents capable of local reasoning and inference, thereby enhancing speed, privacy, and reliability in distributed environments. The curriculum focuses on performance tuning, low-latency design, and hardware–software integration.

This instructor-led, live training (available online or onsite) targets intermediate-level professionals seeking to implement and optimize on-device agentic systems using Python and edge AI frameworks.

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

• Grasp the architecture and challenges of running agentic AI on edge devices.
• Design lightweight agent loops tailored for 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 operation.

Format of the Course

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

Course Customization Options

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

Agentic AI encompasses systems capable of acting autonomously to achieve specific objectives by integrating reasoning capabilities, memory retention, and tool utilization. This course offers a structured introduction to the core concepts of agentic AI, emphasizing prompt engineering, architectural design patterns, and best practices for responsible deployment. Participants will acquire the foundational knowledge necessary to build, guide, and deploy agents effectively and securely.

This instructor-led, live training is available in online or onsite formats and is designed for beginner to intermediate-level professionals aiming to understand how to design, prompt, and manage responsible agentic systems through practical frameworks and real-world examples.

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

• Explain the fundamental principles and lifecycle of agentic AI systems.
• Apply prompt engineering techniques to ensure effective task completion.
• Design simple agent workflows utilizing tool access and decision logic.
• Implement safety, governance, and responsible-use considerations within AI agents.
• Build a prototype agent using open frameworks and Python.

Format of the Course

• Interactive lectures accompanied by guided demonstrations.
• Hands-on exercises and coding practice.
• Collaborative discussions and case-based activities.

Course Customization Options

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

Agentic AI for Business Automation is a practical, hands-on course designed to equip participants with the skills to design, integrate, and scale AI-driven agents for real-world business operations. The curriculum focuses on identifying automation opportunities, connecting various tools, and developing practical use cases across key areas such as customer service, supply chain management, and marketing workflows.

This instructor-led, live training session (available online or onsite) is tailored for intermediate-level professionals aiming to implement AI-powered automation using no-code, low-code, and Python-based methodologies.

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

• Recognize key areas where agentic AI can enhance process efficiency and drive innovation.
• Map existing workflows to determine their suitability for AI agent integration.
• Execute automation strategies through APIs and orchestration platforms.
• Seamlessly integrate AI models into real business scenarios to achieve measurable outcomes.
• Establish governance frameworks and monitoring structures for AI-driven operations.

Course Format

• Engaging lectures complemented by practical demonstrations.
• Hands-on exercises and guided project work.
• Live implementation exercises within a sandbox automation environment.

Customization Options

• To request a customized training session for this course, please contact us to make arrangements.

This course delves into the design, coordination, and implementation of multi-agent systems (MAS) using Python. Participants will learn how to construct agents that communicate, collaborate, and adapt to achieve shared objectives within complex, dynamic environments.

This instructor-led live training (available online or onsite) is designed for advanced professionals aiming to develop and deploy multi-agent systems for intelligent automation, simulation, and decision-making applications.

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

• Grasp the architecture and core principles of multi-agent systems.
• Develop agents capable of communication, coordination, and negotiation.
• Implement distributed environments for agent interactions.
• Apply reinforcement learning and planning techniques in multi-agent contexts.
• Simulate cooperative and competitive agent behaviours.
• Design hybrid workflows that integrate humans with intelligent agents.

Course Format

• Instructor-led lectures and live demonstrations.
• Hands-on exercises utilising open-source agent frameworks.
• Applied group project simulating a multi-agent scenario.

Course Customisation Options

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

This course delves into the core principles and practical implementation of reinforcement learning (RL) and sequential decision-making within agentic AI systems. Participants will learn to design, train, and evaluate agents that interact dynamically with their environments to achieve long-term objectives through continuous learning and adaptation.

Delivered as an instructor-led live training (available online or onsite), this programme is tailored for advanced-level engineers and researchers seeking to integrate reinforcement learning and planning algorithms into agentic systems for applications in automation, robotics, and adaptive reasoning.

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

• Grasp the mathematical foundations underpinning reinforcement learning and decision-making processes.
• Implement essential RL algorithms, including DQN, PPO, and A3C, using Python and PyTorch.
• Model environments using OpenAI Gym and design custom simulation scenarios.
• Train, evaluate, and debug agents for both continuous and discrete control tasks.
• Apply reinforcement learning techniques to agentic AI use cases in robotics and planning.
• Balance exploration, exploitation, and safety constraints during real-world deployment.

Course Format

• Instructor-led lectures accompanied by live coding demonstrations.
• Hands-on exercises utilizing open-source frameworks and simulation environments.
• An applied project focused on integrating decision-making capabilities into an agentic AI system.

Course Customization Options

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

This course addresses the scaling, operationalization, and management of agentic AI systems within production environments, with a strong emphasis on reliability, observability, and cost efficiency.

Delivered as instructor-led live training (available online or onsite), this programme is designed for advanced-level professionals seeking to construct resilient, observable, and cost-optimized pipelines for large-scale agentic systems.

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

• Design scalable architectures suited for agentic AI workloads.
• Implement observability and monitoring frameworks specifically tailored to agent behaviour and interactions.
• Apply performance tuning and resource optimization techniques for long-running agent processes.
• Manage costs and mitigate 'agent sprawl' through effective policy, orchestration, and automation.
• Integrate MLOps best practices for the continuous deployment, versioning, and rollback of agentic services.

Course Format

• Hands-on, engineering-focused sessions supported by live infrastructure examples.
• Interactive discussions on architectural trade-offs and observability challenges.
• Capstone exercise: deploying and monitoring a cost-controlled, production-grade agentic system.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

WrenAI empowers organizations to move beyond static dashboards, embracing conversational analytics and embedded generative BI. This shift demands meticulous adoption planning, the migration of existing assets, and robust change management strategies.

This instructor-led, live training (available online or onsite) is designed for intermediate-level BI and data platform professionals looking to modernize their legacy BI systems using WrenAI.

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

• Assess legacy BI environments and pinpoint opportunities for modernization.
• Plan and execute the migration from static dashboards to WrenAI.
• Implement conversational analytics and embedded GenBI capabilities.
• Lead organizational change management efforts related to BI modernization.

Course Format

• Interactive lectures and discussions.
• Hands-on exercises focused on migration and adoption planning.
• Practical labs covering conversational analytics and embedded GenBI.

Course Customization Options

• For customized training requests regarding this course, please contact us to arrange details.

This course explores governance, identity management, and adversarial testing for agentic AI systems, with a focus on enterprise-safe deployment patterns and practical red-teaming techniques.

This instructor-led, live training (available online or onsite) is designed for advanced-level practitioners who aim to design, secure, and evaluate agent-based AI systems within production environments.

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

• Define governance models and policies for safe agentic AI deployments.
• Design non-human identity and authentication flows for agents, ensuring least-privilege access.
• Implement access controls, audit trails, and observability mechanisms tailored to autonomous agents.
• Plan and execute red-team exercises to identify misuse, escalation paths, and data exfiltration risks.
• Mitigate common threats to agentic systems through policy, engineering controls, and monitoring.

Course Format

• Interactive lectures and threat-modeling workshops.
• Hands-on labs covering identity provisioning, policy enforcement, and adversary simulation.
• Red-team/blue-team exercises and an end-of-course assessment.

Course Customization Options

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

Python serves as the foundational language for developing and orchestrating autonomous AI agents. This course emphasizes practical implementation, leveraging modern SDKs and frameworks such as LangChain and AutoGen to construct, interconnect, and manage agent workflows.

This instructor-led live training (available online or onsite) is designed for intermediate-level backend, platform, and ML engineers seeking to implement and orchestrate autonomous agents using Python tooling and APIs.

Upon completion of this training, participants will be capable of:

• Setting up and configuring Python environments tailored for agentic systems.
• Utilizing popular agent SDKs, including LangChain and AutoGen, to develop functional agents.
• Integrating tools and APIs to expand agent capabilities.
• Orchestrating multi-agent workflows and communication patterns.
• Applying best practices for debugging, testing, and maintaining agentic codebases.

Course Format

• Interactive lectures and discussions.
• Hands-on programming exercises and live demonstrations.
• Practical projects focusing on end-to-end agent workflow creation.

Course Customization Options

• To request customized training for this course, please contact us to make arrangements.

WrenAI equips finance teams with the capabilities to model Key Performance Indicators (KPIs), integrate standardized metrics, and design dashboards that adhere to regulatory requirements and audit standards.

This instructor-led live training, available online or onsite, targets intermediate to advanced finance professionals seeking to leverage WrenAI for constructing compliant financial data models and dashboards that facilitate decision-making and risk management.

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

• Model financial KPIs and metrics within WrenAI.
• Construct dashboards that align with regulatory and audit requirements.
• Integrate WrenAI with finance data sources to enable real-time reporting.
• Apply best practices for financial analytics and risk monitoring.

Course Format

• Interactive lectures and discussions.
• Practical exercises involving financial data models.
• Hands-on labs focused on dashboard design and compliance reporting.

Course Customization Options

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

This course provides practical engineering methodologies for designing, constructing, testing, and deploying autonomous (agentic) systems using Python. It explores the agent lifecycle, tool integrations, memory and state management, orchestration patterns, safety controls, and critical production considerations.

Delivered as an instructor-led, live training session (available online or onsite), this program is tailored for intermediate to advanced ML engineers, AI developers, and software engineers aiming to build robust, production-ready autonomous agents using Python.

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

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

Course Format

• Interactive lectures and discussions.
• Hands-on labs involving the construction of agents with Python and popular SDKs.
• Project-based exercises that result in deployable prototypes.

Course Customization Options

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

WrenAI facilitates the conversion of natural language into SQL and supports AI-driven analytics, enabling faster and more intuitive data access. For enterprise environments, rigorous quality assurance and observability practices are critical to guaranteeing accuracy, reliability, and regulatory compliance.

This instructor-led, live training (available online or onsite) is designed for advanced data and analytics professionals who wish to assess query accuracy, apply prompt tuning strategies, and implement observability practices to monitor WrenAI in production environments.

Upon completion of this training, participants will be capable of:

• Assessing the accuracy and reliability of natural language to SQL outputs.
• Applying prompt tuning techniques to enhance system performance.
• Monitoring for drift and analysing query behaviour over time.
• Integrating WrenAI with logging and observability frameworks.

Course Format

• Interactive lectures and discussions.
• Practical exercises focusing on evaluation and tuning techniques.
• Hands-on labs covering observability and monitoring integrations.

Customisation Options

• To request a customised version of this course, please contact us to make arrangements.

Agentic AI represents a paradigm where artificial intelligence systems autonomously plan, reason, and utilize tools to achieve specific objectives within defined constraints.

This instructor-led live training, available either online or onsite, is designed for intermediate-level healthcare and data teams aiming to design, assess, and govern agentic AI solutions for both clinical and operational applications.

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

• Articulate the core concepts and constraints of agentic AI within healthcare settings.
• Develop secure agent workflows that incorporate planning, memory, and tool integration.
• Construct retrieval-augmented agents capable of processing clinical documents and knowledge bases.
• Assess, monitor, and govern agent behaviour through the implementation of guardrails and human-in-the-loop controls.

Course Format

• Interactive lectures complemented by facilitated discussions.
• Guided laboratory sessions and code walkthroughs conducted in a sandbox environment.
• Scenario-based exercises focusing on safety, evaluation, and governance.

Course Customization Options

• For those interested in a tailored version of this course, please reach out to us to arrange your custom training.

WrenAI is an AI-driven analytics platform designed to connect data, model insights, and generate dashboards. In enterprise environments, robust governance and security are critical to ensuring safe and compliant adoption.

This instructor-led, live training (online or onsite) is aimed at advanced-level enterprise professionals who wish to implement governance, compliance, and security patterns for WrenAI at scale.

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

• Design and implement permissioning models in WrenAI.
• Apply auditability and monitoring practices for compliance.
• Set up secure environments with enterprise-level controls.
• Roll out WrenAI safely across large organizations.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with governance and security configurations.
• Practical exercises simulating enterprise rollout scenarios.

Course Customization Options

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

This instructor-led, live training in Lisbon (available online or onsite) is designed for intermediate-level AI developers and automation specialists seeking to integrate agentic capabilities into AI-powered applications.

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

• Grasp the fundamental principles of agentic AI and autonomous decision-making.
• Develop goal-oriented AI agents utilizing self-optimization methods.
• Implement multi-agent collaboration frameworks for tackling complex challenges.
• Improve AI-human engagement through adaptive user experiences.
• Deploy agentic AI models within real-world applications.

The WrenAI Spreadsheets and Metrics Library facilitate rapid reporting by leveraging AI-driven spreadsheet workflows and a repository of pre-built, cross-platform business metrics.

This instructor-led training session, available online or onsite, targets beginner to intermediate operations professionals looking to accelerate their reporting and analysis capabilities using WrenAI Spreadsheets and the Metrics Library.

Upon completing this training, participants will be capable of:

• Developing AI-enhanced spreadsheets for data analysis and reporting purposes.
• Utilizing the WrenAI Metrics Library to establish standardized Key Performance Indicators (KPIs).
• Linking spreadsheets to various data sources to ensure real-time updates.
• Designing automated workflows to streamline operational reporting processes.

Course Format

• Interactive lectures and discussions.
• Practical, hands-on experience in building spreadsheets with WrenAI.
• Practical exercises focused on metrics and KPI reporting.

Course Customization Options

• For those interested in requesting a tailored training for this course, please contact us to arrange the details.

This instructor-led, live training in Lisbon (online or onsite) targets advanced professionals aiming to develop and optimize multi-agent systems using Agentic AI frameworks.

Upon completion, 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 Lisbon (online or on-site) is designed for advanced-level professionals seeking to harness Agentic AI for enterprise-scale automation and strategic AI adoption.

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

• Grasp the role of Agentic AI in enterprise applications.
• Integrate autonomous AI agents with enterprise systems.
• Optimize AI-driven workflows for scalability and efficiency.
• Ensure compliance, security, and governance in AI automation.
• Develop AI-driven business strategies for digital transformation.

WrenAI Cloud offers a contemporary platform designed to connect data sources, model data, and construct interactive dashboards.

This instructor-led live training, available either online or onsite, targets beginner to intermediate data professionals looking to master the setup of WrenAI Cloud, data modelling, and the visualization of insights within dashboards.

Upon completing this training, participants will be capable of:

• Setting up and configuring WrenAI Cloud environments.
• Linking WrenAI Cloud to various data sources.
• Modelling data and defining relationships for analytical purposes.
• Developing interactive dashboards to derive business insights.

Course Format

• Interactive lectures and discussions.
• Practical experience with cloud platform configuration and data modelling.
• Hands-on exercises focused on dashboard creation and visualization.

Customization Options

• For tailored training on this course, please get in touch to arrange your requirements.

This instructor-led, live training in Lisbon (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.

WrenAI is an open-source generative BI tool that enables natural language to SQL conversion and semantic data modeling.

This instructor-led, live training (online or onsite) is aimed at advanced-level data engineers, analytics engineers, and ML engineers who wish to build robust semantic layers, tune prompts, and ensure reliable SQL generation.

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

• Implement semantic models for consistent metric definitions across teams.
• Optimize text-to-SQL performance for accuracy and scalability.
• Configure and enforce guardrails to avoid invalid or risky queries.
• Integrate WrenAI OSS into data pipelines and analytics workflows.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• 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 Lisbon (online or onsite) is designed for AI engineers, ML researchers, and developers at an intermediate level who aim to build and implement Agentic AI systems in real-world applications.

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

• Grasp the fundamental principles of Agentic AI systems.
• Deploy AI agents capable of autonomous reasoning and action.
• Integrate Agentic AI with APIs and third-party services.
• Optimize interactions among multiple agents to handle complex tasks.
• Tackle ethical, security, and scalability challenges inherent in Agentic AI.

WrenAI empowers SaaS providers to embed generative business intelligence (GenBI) directly within their customer-facing applications. This course equips SaaS teams with the expertise to integrate Wren AI via its Embedded API, configure white-label analytics, and manage multi-tenant deployments effectively.

This instructor-led, live training (available online or onsite) is designed for intermediate to advanced SaaS product leaders, data engineers, and full-stack developers looking to implement WrenAI as an embedded analytics solution within their SaaS ecosystems.

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

• Integrate WrenAI using the Embedded API for customer-facing applications.
• Implement white-label conversational BI with branding and customization.
• Design secure and scalable multi-tenant deployments.
• Monitor usage, optimize performance, and ensure compliance in SaaS environments.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs using WrenAI Embedded API.
• Workshop: design and deploy a white-label analytics feature for a SaaS use case.

Course Customization Options

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

This instructor-led, live training in Lisbon (available online or onsite) caters to beginner-level professionals seeking to understand the core principles of Agentic AI, its capabilities, and its potential industry impact.

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

• Understand the core principles of Agentic AI.
• Differentiate between traditional AI and autonomous AI agents.
• Explore real-world applications of Agentic AI in various industries.
• Assess the benefits and challenges of deploying autonomous AI systems.
• Analyze the ethical and security considerations of Agentic AI.

WrenAI is a conversational analytics platform that translates natural-language queries into reliable analytics, enabling non-technical teams to generate insights quickly and consistently.

This instructor-led, live training (online or onsite) is aimed at intermediate-level product managers, analysts, and data champions who wish to adopt conversational analytics and build self-service BI capabilities with WrenAI.

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

• Design conversational analytics workflows that surface reliable product insights.
• Create and maintain a standardized metrics layer for consistent reporting.
• Use natural-language to SQL features effectively to answer product questions.
• Embed WrenAI-driven self-service dashboards and guardrails in product workflows.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with Wren AI and sample datasets.
• Workshop: build a self-service dashboard and conversational query set.

Course Customization Options

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

AI agents are transitioning from experimental prototypes to autonomous production systems that operate across text, image, speech, and tool-driven workflows. This shift demands higher standards for engineering rigour, adversarial robustness, and regulatory compliance. This instructor-led training guides experienced practitioners through the entire agent lifecycle, covering the design of single and multi-agent systems, the integration of multi-modal perception, and the orchestration of coordinated agent behaviour using contemporary frameworks. Through progressive Python-based practical labs, participants will construct a production-grade multi-agent system, which they will then stress-test using adversarial techniques and the Adversarial Robustness Toolbox. The course concludes with guidance on aligning with NIST AI RMF, ISO/IEC 42001, the EU AI Act, and GDPR, as well as securing deployment, monitoring, and incident response protocols. By the end, participants will be equipped to deploy agents that are capable, defensible, and compliant.

This instructor-led live training in Lisbon (online or onsite) is designed for beginner to intermediate developers and cloud practitioners who wish to use Alibaba Cloud to build AI agents that can automate tasks, answer queries, and integrate with business systems.

By the end of this training, participants will be able to: comprehend AI agent architecture on Alibaba Cloud, construct a basic agent workflow, link an agent to enterprise knowledge and tools, and deploy and monitor an agent within a cloud environment.