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Agentic AI Content for Practitioners (Teams: Data)

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Ce cours n'est pas disponible en Français (France)

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Agentic AI Content for Practitioners (Teams: Data)

Instructeur : Hurix Digital

Inclus avec

3 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

4 heures à compléter

Planning flexible

Apprenez à votre propre rythme

3 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

4 heures à compléter

Planning flexible

Apprenez à votre propre rythme

Compétences que vous acquerrez

Catégorie : Software Design Patterns
Catégorie : Agentic systems
Catégorie : AI Integrations
Catégorie : Continuous Improvement Process
Catégorie : Scalability
Catégorie : Automation
Catégorie : Generative AI Agents
Catégorie : Advanced Analytics
Catégorie : Artificial Intelligence
Catégorie : Data Quality
Catégorie : Enterprise Architecture
Catégorie : Performance Tuning

Outils que vous découvrirez

Catégorie : AI Orchestration
Catégorie : AI Workflows
Catégorie : Agentic Workflows

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Récemment mis à jour !

décembre 2025

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Enseigné en Anglais

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Il y a 3 modules dans ce cours

Agentic AI Content for Practitioners (Teams: Data) is an intermediate-level course designed to equip data professionals, software engineers, and business analysts with the knowledge and skills to design, implement, and optimize AI agents for intelligent data automation. As organizations transition from experimental AI deployments to enterprise-scale implementations, this course provides the practical expertise needed to build reliable, scalable agent systems that deliver measurable business value.

Through hands-on labs, real-world case studies, and interactive projects, you'll learn to transform manual data operations into intelligent, adaptive systems. The course covers everything from agent architecture fundamentals to advanced optimization strategies, preparing you to lead AI agent initiatives in your organization. You'll explore popular frameworks, design patterns, and deployment strategies while addressing critical considerations like error handling, scalability, and enterprise integration. Whether you're automating data quality monitoring, building predictive analytics systems, or creating intelligent customer service agents, this course provides the foundation you need to succeed in the rapidly evolving landscape of AI-powered data automation.

Détails du module

This foundational lesson introduces learners to the core concepts of AI agents, their architectural components, and their specific applications in data automation. Through real-world examples and hands-on exploration, learners will understand what makes AI agents effective for automating data workflows and identify key use cases across industries.

Inclus

4 vidéos3 lectures1 devoir

4 vidéosTotal 22 minutes

Introduction and Welcome4 minutes
What Makes an AI Agent "Intelligent"?6 minutes
Types of AI Agents: From Simple to Sophisticated5 minutes
Core Components of AI Agent Architecture8 minutes

3 lecturesTotal 30 minutes

Welcome to the Course: Course Overview10 minutes
AI Agents Transforming Data Automation Across Industries10 minutes
Framework Landscape: Choosing the Right Tools for Agent Development10 minutes

1 devoirTotal 15 minutes

HOL: Analyze and Map AI Agent Components in Real-World Scenarios15 minutes

This lesson focuses on practical implementation of AI agents for data automation. Learners will explore popular frameworks, design patterns, and deployment strategies. Through hands-on labs and case studies, they'll learn to build, test, and deploy AI agents for real-world data workflows while addressing common challenges like error handling, scalability, and integration with existing systems.

Inclus

3 vidéos1 lecture1 devoir

This final lesson focuses on advanced topics in AI agent deployment, including performance optimization, scalability strategies, and enterprise integration. Learners will explore monitoring and evaluation frameworks, learn to scale agent systems for production environments, and develop strategies for continuous improvement and maintenance. The lesson culminates in a comprehensive capstone project and assessment.