AI Learning & Education

AI+ Learning & Development

This certification teaches AI in education, covering Machine Learning, NLP, ethics, and trends. Participants design adaptive systems and complete a capstone project to drive AI-driven innovation in learning.

Duration

1 Day (8 hours)

Targeted Audience

Workforce Development Expert

Learning and Development Specialist

Corporate Training Developer

Educational Program Designer

Prerequisites for Success

A basic understanding of artificial intelligence concepts and terminologies
Proficiency in using digital tools and platforms for educational purposes
Familiarity with learning theories and instructional design principles
Some experience in educational or training roles, such as teaching, content development, or instructional design
A willingness to engage with technical subjects and apply AI technologies in the context of learning and development

Modules | 8

Examination | 1

Passing Score | 70%

COURSE AGENDA

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.