Online or onsite, instructor-led live Agentic AI training courses demonstrate through interactive hands-on practice how to use autonomous decision-making systems to automate tasks, make data-driven decisions, and optimize business processes.
Agentic AI training is available as "online live training" or "onsite live training". Online live training (aka "remote live training") is carried out by way of an interactive, remote desktop. Riga onsite live Agentic AI trainings can be carried out locally on customer premises or in NobleProg corporate training centers.
NobleProg -- Your Local Training Provider
Riga, Old Town
Konventa Seta, 9/11 Kaleju iela, Riga, Latvia
Located directly on Riga’s Old Town, only 100 m from the Riga's Dom Cathedral.
This instructor-led, live training in Riga (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.
This instructor-led, live training in Riga (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 Riga (online or onsite) is aimed at advanced-level professionals who wish to leverage Agentic AI for enterprise-scale automation and strategic AI adoption.
By the end of this training, participants will be able to:
Understand 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.
This instructor-led, live training in Riga (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.
This instructor-led, live training in Riga (online or onsite) is aimed at intermediate-level AI engineers, ML researchers, and developers who wish to build and implement Agentic AI systems in real-world applications.
By the end of this training, participants will be able to:
Understand the core principles of Agentic AI systems.
Implement AI agents capable of autonomous reasoning and action.
Integrate Agentic AI with APIs and third-party services.
Optimize multi-agent interactions for complex tasks.
Address ethical, security, and scalability challenges in Agentic AI.
This instructor-led, live training in Riga (online or onsite) is aimed at beginner-level professionals who wish to understand the fundamental principles of Agentic AI, its capabilities, and its potential impact on industries.
By the end 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.
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