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AI in Education: Adaptive Learning & Personalized Pathways

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

Nous sommes actuellement en train de le traduire dans plus de langues.

AI in Education: Adaptive Learning & Personalized Pathways

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

Ce que vous apprendrez

Data-driven personalization uses behavior and performance metrics to scale tailored learning for diverse populations
AI content requires systematic bias detection and inclusivity validation to ensure equitable, high-quality learning for all.
L&D transformation pairs real-time analytics with content workflows to identify performance gaps and trigger proactive interventions
Adaptive learning succeeds when AI augments human expertise, requiring designers to master prompt engineering and curation.

Compétences que vous acquerrez

Catégorie : Responsible AI
Catégorie : AI Personalization
Catégorie : Artificial Intelligence
Catégorie : Driving engagement
Catégorie : Education Software and Technology
Catégorie : Analytical Skills
Catégorie : Analytics
Catégorie : Data Ethics
Catégorie : Data Analysis
Catégorie : Data-Driven Decision-Making
Catégorie : Quality Assurance

Outils que vous découvrirez

Catégorie : Generative AI
Catégorie : Learning Management Systems
Catégorie : Prompt Engineering

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Récemment mis à jour !

avril 2026

Évaluations

7 affectations¹

Noté par l'IA voir l'avis de non-responsabilité

Enseigné en Anglais

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Il y a 3 modules dans ce cours

AI is transforming education by creating truly personalized learning experiences that adapt to each learner's unique needs and progress. This Short Course was created to help Human Resources professionals accomplish adaptive learning implementation with quality controls and learner-centered analytics. By completing this course, you'll be able to configure adaptive engines that automatically route learners based on performance data, identify content gaps through engagement metrics, and ensure AI-generated materials meet inclusivity standards.

By the end of this course, you will be able to: • Apply adaptive learning engine settings to map curriculum objectives into personalized learner pathways with mastery checkpoints • Analyze engagement analytics such as drop-off rate and time-on-task to identify content segments requiring redesign • Evaluate AI-generated lesson drafts against bias and hallucination guardrails, revising prompts to meet quality and inclusivity standards This course is unique because it combines hands-on platform configuration with data-driven optimization and AI ethics, addressing real-world L&D implementation challenges. To be successful in this project, you should have experience with learning management systems and basic data interpretation skills.