Whether delivered online or on-site, our instructor-led live CrewAI training programmes focus on practical, interactive exercises. These sessions demonstrate how to effectively utilise CrewAI to construct and coordinate multi-agent AI systems, enabling collaborative task execution and process automation.
CrewAI training is offered in two formats: "online live training" or "onsite live training". Online live training (also referred to as "remote live training") is conducted via an interactive remote desktop environment. Onsite live training can be delivered locally at your premises in Gaia or within NobleProg corporate training centres in Gaia.
NobleProg -- Your Local Training Provider
Holiday Inn Porto - Gaia
220, Rua Diogo Macedo, 220, Vila Nova de Gaia 4400-107 , Gaia, Portugal
From Porto by Metro
If you're coming from Porto city centre:
Take the Metro Line D (yellow line) toward Vila d’Este.
Get off at João de Deus.
From João de Deus, walk about 13 minutes to: Rua Diogo Macedo 220, 4400-107 Vila Nova de Gaia.
From Vila Nova de Gaia train station
If by “local train station” you mean Vila Nova de Gaia-Devesas:
The address is approximately 12 minutes walking from Vila Nova de Gaia station according to the accommodation's location information.
You can therefore walk directly rather than taking the metro.
This instructor-led, live training in Gaia (online or on-site) is aimed at advanced professionals who wish to build secure and compliant agent workflows using CrewAI in enterprise environments.
By the end of this training, participants will be able to:
Design secure and auditable workflows involving multiple agents.
Implement data privacy strategies within autonomous systems.
Integrate logging, governance, and compliance mechanisms.
Deploy and monitor secure CrewAI-based systems in production environments.
This instructor-led live training in Gaia (online or onsite) is designed for intermediate-level business and AI professionals aiming to create intelligent, domain-specific business agents using CrewAI.
By the end of this training, participants will be able to:
Understand the architecture of CrewAI and its relevance in business use cases.
Create business-oriented agents using roles, tools, and memory.
Build agent crews that collaborate to perform business workflows.
Apply CrewAI in practical scenarios such as finance, marketing, and customer support.
This instructor-led live training in Gaia (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to scale CrewAI systems, integrate with enterprise tools, and deploy automation solutions in production environments.
By the end of this training, participants will be able to:
Design scalable multi-agent systems using CrewAI.
Integrate agents with enterprise tools like Slack, databases, and APIs.
Implement monitoring, logging, and diagnostics for agent behavior.
Deploy, manage, and scale CrewAI solutions in production environments.
This instructor-led, live training in Gaia (online or onsite) is aimed at advanced-level professionals who wish to design and implement custom multi-agent systems using CrewAI with complex workflows, event triggers, and tool integrations.
By the end of this training, participants will be able to:
Design and build custom AI agents with specialized roles and tools.
This instructor-led live training in Gaia (online or onsite) is aimed at intermediate-level professionals who wish to automate business and technical workflows using CrewAI through real-world use cases and tool integrations.
By the end of this training, participants will be able to:
Understand the architecture and core principles of CrewAI.
This instructor-led, live training in Gaia (online or onsite) targets beginner-level professionals who wish to explore the fundamentals of CrewAI and build simple multi-agent systems.
By the end of this training, participants will be able to:
Understand the architecture and design principles of CrewAI.
Define roles, tasks, and flows within a crew of agents.
Create collaborative workflows using CrewAI's framework.
Build, test, and run basic multi-agent scenarios.
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