AI+ Learning & Development Practitioner™

Ártól 80 000 Ft + Áfa
Önálló online Azonnal kezdhető
Időtartam 8 óra tananyag, önálló tempóban
Nyelv angol
Terület AI Learning & Education

Kinek szól
Mit tartalmaz az ár
Tematika
A vizsgáról

Áttekintés

Miről szól a képzés

A kurzus, a tananyag és a vizsga angol nyelvű. Az alábbi leírás az AI CERTs® eredeti szövege.

Education Innovation: Designed for educators and trainers to leverage AI in learning
Deep Insights: Includes ML, NLP, Data Analytics, and adaptive learning strategies
Capstone Delivery: Build AI-powered learning solutions tailored to diverse needs
Ethical Education: Address ethics, data-driven instruction, and emerging trends

Előfeltételek

Basic knowledge of computer science and statistics, data analysis, fundamental AI/ML concepts, Python and R.

Célcsoport

Kinek szól

Learning and Development Professionals: Enhance employee training and development strategies using AI-driven learning tools.

Instructional Designers: Apply AI techniques to design personalized learning experiences and optimize content delivery.

AI Specialists: Leverage AI to create innovative solutions for improving learning outcomes and enhancing educational platforms.

HR Professionals & Organizational Development Experts: Implement AI-powered systems to analyze employee performance and optimize training programs.

Students & New Graduates: Build essential skills in AI and learning technologies to excel in the evolving field of education and training.

Az árban

Mit tartalmaz az ár

Önálló tempójú online kurzus, a teljes tananyaggal
A hivatalos AI CERTs® vizsga
Digitális badge a sikeres vizsga után

Tananyag

Tematika

Course Overview

Course Introduction Preview

Module 1: Introduction to Artificial Intelligence (AI) in Education

1.1 Overview of Artificial Intelligence 1.2 AI’s Role in Education and Training 1.3 Impact of AI on Educational Content Creation 1.4 AI in Assessment and Feedback 1.5 Ethical Considerations and Challenges

Module 2: Machine Learning Fundamentals

2.1 Introduction to Machine Learning 2.2 Supervised Learning 2.3 Unsupervised Learning 2.4 Reinforcement Learning 2.5 Machine Learning in Practice

Module 3: Natural Language Processing (NLP) for Educational Content

3.1 Fundamentals of NLP in Education 3.2 Content Analysis and Enhancement 3.3 Personalized Learning and Adaptive Content 3.4 Assessment and Feedback Automation

Module 4: AI-Driven Content Creation and Curation

4.1 AI in Generating Educational Content 4.2 Adaptive Learning Materials Creation 4.3 Dynamic Assessment Item Generation 4.4 Curating Educational Resources 4.5 Challenges and Ethical Considerations in AI-Driven Content

Module 5: Adaptive Learning Systems

5.1 Foundations of Adaptive Learning 5.2 Designing Adaptive Learning Systems 5.3 Implementation Strategies 5.4 Assessment and Evaluation in Adaptive Systems 5.5 Ethical and Privacy Considerations

Module 6: Ethics and Bias in AI for L&D

6.1 Understanding AI Ethics in L&D 6.2 Privacy Concerns in AI-Driven L&D 6.3 Bias and Fairness in AI Assessments 6.4 Ethical AI Use and Learner Engagement 6.5 Future Challenges and Opportunities

Module 7: Emerging Technologies and Future Trends

7.1 Augmented Reality (AR) in Education 7.2 Virtual Reality (VR) in Learning Environments 7.3 AI-Driven Personalized Learning 7.4 Blockchain in Education 7.5 Emerging AI Technologies in Educational Research and Development

Module 8: Implementation and Best Practices

8.1 Strategic Planning for AI Integration 8.2 Selecting the Right AI Tools 8.3 Implementing AI Solutions 8.4 Monitoring and Evaluating Impact 8.5 Ethical Use and Data Governance

Optional Module: AI Agents for Learning & Development

1. Understanding AI Agents 2. Case Studies 3. Hands-On Practice with AI Agents

Vizsga

A vizsgáról

50 Kérdés
90 perc Időkeret
70% Ponthatár

Online proctored exam

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