Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
AI in Education: Overview gives you a clear, balanced map of how machine learning is changing teaching and learning. You explore the major applications — adaptive and personalised learning, intelligent tutoring, automated assessment, and learning analytics — and how each supports students and educators. The course pairs the opportunities with the real questions: fairness, data privacy, and keeping the human at the centre of a fundamentally human process. You finish with a grounded understanding of where AI genuinely helps education. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This overview course covers AI in education — adaptive learning, tutoring, assessment and analytics, and the opportunities and risks of AI across teaching and learning.
📋 Course Objectives
1. Map the major applications of AI in education.
2. Understand adaptive learning and tutoring.
3. Explain automated assessment and analytics.
4. Weigh fairness, privacy and the human role.
5. Judge where AI genuinely helps learning.
👥 Who Should Enroll?
• Educators and instructional designers
• Ed-tech and administration staff
• Education researchers
• Students of learning technology
🚀 Key Learning Outcomes
• A grounded overview of AI in education.
• The ability to evaluate ed-tech AI.
• A critical, learner-centred perspective.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Introduction to AI in Education
What is AI in Education? • Role of Technology in Modern Learning • Traditional vs AI-Driven Education Systems • Applications of AI in Education
Educational Data and AI
Types of Educational Data • Student Performance and Learning Analytics • How AI Uses Learning Data • Importance of Data Privacy
AI Applications in Learning
Personalized Learning Systems • Automated Grading and Assessment • AI Tutors and Chatbots in Education • Learning Recommendation Systems
Benefits and Challenges
Advantages of AI in Education • Challenges in Implementation • Ethical Concerns and Bias • Limitations of AI in Learning Systems
Future Scope and Opportunities
AI in Online Learning and EdTech • Smart Classrooms and Digital Learning • Career Opportunities in AI and Education • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Artificial Intelligence |
| Covered Tool / Platform | Education Technology |
| Covered Tool / Platform | Learning Analytics |
| Covered Tool / Platform | Personalized Learning |
| Covered Tool / Platform | AI Applications |
Frequently Asked Questions
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