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Avis du cours AI Agents for Leaders par Prof. Dr. Ana-Maria Olteteanu

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Understand, Lead, and Strategically Apply AI Agents Across Industries — Without Writing Code

Format d'apprentissage Online Course

Sous-catégorie AI Agents

Prix du cours $19.99 (list $9.99)

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Understand, Lead, and Strategically Apply AI Agents Across Industries — Without Writing Code

Qui est Prof. Dr. Ana-Maria Olteteanu ?

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Nombre total d'élèves

454 students

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Langue du cours

English

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Que apprend-on dans le cours de Prof. Dr. Ana-Maria Olteteanu ?

Distinguish between rule-based bots, RPA systems, and modern AI agents.

Understand the foundations of Agents and Agentic Architectures

Identify the main components of Agents and Agent Architectures

Explore what makes an agent “intelligent,” including features like autonomy, memory, planning, and interactivity.

Analyze state-of-the-art applications of agents in domains such as healthcare, enterprise, education, and personal productivity.

Compare leading agent architectures (e.g., Autogen, CrewAI, LangGraph) and learn when to use each.

Understand how to integrate tools, memory systems, and external APIs to enable agents to perceive, reason, and act in real or simulated environments.

See how one can implement agents using open-source frameworks like LangChain, CrewAI, or LangGraph.

Explore concepts such as recursive prompting, self-reflection, planning, negotiation, and agent collaboration.

Design and simulate multi-agent workflows with communication, goal alignment, and safety considerations.

Examine the ethical, technical, and societal challenges of autonomous agents—including embodiment, trust, and permission layers.

Explore cutting-edge research directions and speculate on trends shaping the future of agent technologies.

Design and prototype their own AI agents using open-source frameworks like LangChain, CrewAI, or LangGraph.

Integrate agents into productivity, healthcare, or enterprise workflows with an awareness of memory, safety, planning, and tool use.

Evaluate agent architectures and agent capabilities for internal deployments, product innovation, or research prototyping.

Contribute to multi-agent systems or lead discussions about how AI agents will reshape industries.

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