AI+ Learning & Development™
AI-Enhanced Learning: Where Knowledge Meets Innovation
This course drives education innovation, designed for educators and trainers seeking to leverage AI within modern learning environments. It delivers deep insights into key areas including Machine Learning, Natural Language Processing, Data Analytics, and adaptive learning strategies. Through a capstone delivery, participants design AI-powered learning solutions tailored to diverse learner needs. With a strong ethical education focus, the course explores responsible AI use, data-driven instruction, and emerging trends shaping the future of education.
Enrollment Fee:
MUR 5,980
What You'll Learn
- Course Introduction
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
2.1 Introduction to Machine Learning
2.2 Supervised Learning
2.3 Unsupervised Learning
2.4 Reinforcement Learning
2.5 Machine Learning in Practice
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
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
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
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
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
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
1. Understanding AI Agents
2. Case Studies
3. Hands-On Practice with AI Agents
Prerequisites
- 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.
Exam Details
Duration:
90 minutes
Passing Score:
70% (35/50)
Format:
50 multiple-choice/multiple-response questions
Delivery Method:
Online via proctored exam platform (flexible scheduling)
Unlock Self-Paced Online Learning
- Unlock Self-Paced Online Learning
- Access learning anytime, anywhere, with built-in quizzes to measure progress.
- Enrollment Fee: MUR 5,980