Create an online learning platform using microservices where different modules like courses, students, assessments, and notifications are independent. Integrate AI to adapt course difficulty based on student performance and learning patterns.
Develop microservices for courses, students, assessments, and notifications.
Implement REST APIs for inter-service communication.
Containerize services using Docker and orchestrate using Kubernetes.
Preprocess assessment data and train ML models for adaptive learning.
Integrate AI to dynamically adjust content difficulty per student.
Handle user authentication and role-based access.
Use API Gateway for routing and load balancing.
Test microservices independently and as a full system.
Monitor system for errors, latency, and performance.
Document service architecture, ML model workflow, and deployment processes.
