60-Days Hands-On "AI-Engineering" with "Quiz Platform" Implementation

Introduction

This intensive hands-on curriculum guides students through building a production-grade AI-powered quiz platform with emphasis on backend development, business logic, and software development lifecycle practices. Each day includes concrete coding exercises that build toward a functional application, following proper SDLC methodology.

Key Architectural Components

1. Backend Services

The architecture implements a microservices pattern with clearly defined responsibilities:

• User Service: Handles authentication, user profiles, and session management

• Quiz Service: Manages quiz creation, retrieval, and attempt tracking

• Content Service: Orchestrates AI content generation and verification

• Analytics Service: Processes user performance data and generates insights

• Notification Service: Manages event notifications and alerts

• Caching Service: Optimizes response times for frequently accessed content

2. AI Components

The AI subsystem is architected with multiple specialized components:

• Content Generation Service: Transforms topics into structured quiz questions

• Content Verification Service: Ensures factual accuracy and educational value

• Difficulty Engine: Implements progressive difficulty algorithms

• AI Model Abstraction Layer: Provides vendor-independence for AI services

3. Data Flow Design

The data flow follows a structured pattern:

1. User requests a quiz on a specific topic

2. Quiz service initiates content generation through the AI service

3. AI generates questions using external models with optimized prompts

4. Content verification ensures accuracy and educational value

5. Verified questions are stored in the database

6. Quiz session is created with progressive difficulty settings

7. User interacts with questions in sequence

8. Performance is analyzed to adjust difficulty dynamically

9. Analytics service records performance metrics for future sessions

   

4. Progressive Difficulty Implementation

The state machine for difficulty progression shows:

• Initial assessment of user knowledge level

• Six progressive difficulty levels from basic recall to expert knowledge

• Continuous performance analysis after each question

• Dynamic difficulty adjustments based on performance patterns

• Protection against rapid difficulty changes to maintain learning engagement

  

Technology Stack and Implementation Considerations

Backend Technologies

• Node.js/Express: Primary backend platform

• MongoDB: Document database for flexible schema evolution

• Redis: Caching layer for performance optimization

• ElasticSearch: For search capabilities and analytics

• JWT: Token-based authentication

AI Integration

• OpenAI/Claude APIs: External AI models for content generation

• Custom Model Integration: For specialized educational content

• Prompt Templates: Standardized templates for consistent outputs

• Caching Strategy: To optimize AI inference costs and performance

DevOps and Infrastructure

• Docker: Containerization for consistent environments

• Kubernetes: Orchestration for scaling and management

• CI/CD Pipeline: Automated testing and deployment

• Monitoring Stack: Comprehensive system observability

This architecture provides a solid foundation for implementing the 60-day learning plan, with a focus on backend development, business logic, and the integration of AI capabilities for an educational quiz platform.

Learning Objectives

By completing this 60-day program, you will:

• Master backend architecture and business logic implementation for AI applications

• Develop practical skills in database design, API development, and system integration

• Gain hands-on experience with the complete software development lifecycle

• Build a production-ready AI quiz platform with progressive difficulty features

• Learn DevOps practices for deploying and maintaining backend services

Day-by-Day Learning Plan

Week 1: Project Setup and Backend Foundations

Day 1: Requirements Analysis and Project Setup

• Theory: Software Development Lifecycle overview and requirements gathering

• Coding Exercise: Create a detailed requirements document with functional/non-functional requirements for the quiz platform

• Technical Task: Set up development environment (Node.js, Git, VS Code) and initialize GitHub repository with proper structure

Day 2: System Architecture Design

• Theory: Backend architecture patterns and microservices

• Coding Exercise: Design and document system architecture diagram with all components

• Technical Task: Create folder structure for backend services with RESTful API patterns

Day 3: Database Schema Design

• Theory: Data modeling and relationships for quiz applications

• Coding Exercise: Create complete Entity-Relationship Diagram for the platform

• Technical Task: Implement MongoDB schemas for users, quizzes, questions, and attempts with proper validation

Day 4: User Authentication Service

• Theory: Authentication flows and security best practices

• Coding Exercise: Implement JWT-based authentication with password hashing

• Technical Task: Build registration, login, and session management endpoints with proper error handling

Day 5: Core Quiz Service - Data Layer

• Theory: Repository pattern and data access layers

• Coding Exercise: Implement quiz repository with CRUD operations

• Technical Task: Create database queries with indexing optimization for quiz retrieval

Day 6: Core Quiz Service - Business Logic

• Theory: Business logic separation and service layer patterns

• Coding Exercise: Implement quiz service with business rules for creation and retrieval

• Technical Task: Build quiz management endpoints with validation and error handling

Day 7: Quiz Session Management

• Theory: Stateful vs. stateless session management

• Coding Exercise: Design and implement quiz attempt tracking service

• Technical Task: Create endpoints for starting, saving, and completing quiz attempts

Week 2: AI Integration - Backend Focus

Day 8: AI Service Architecture

• Theory: Integration patterns for AI services

• Coding Exercise: Design AI service architecture with proper separation of concerns

• Technical Task: Implement service skeleton with OpenAI API integration

Day 9: Prompt Engineering Framework

• Theory: Systematic prompt construction and template management

• Coding Exercise: Build a template management system for AI prompts

• Technical Task: Create prompt templates for different question types with variables

Day 10: Question Generation Service

• Theory: Asynchronous processing for content generation

• Coding Exercise: Implement question generation service with retry logic

• Technical Task: Build endpoint that accepts topic and returns generated questions

Day 11: Content Verification Service

• Theory: AI output validation and quality control

• Coding Exercise: Design and implement content verification pipeline

• Technical Task: Create verification service that checks factual accuracy and format

Day 12: Topic Analysis Service

• Theory: NLP techniques for topic extraction and categorization

• Coding Exercise: Implement topic analysis and categorization service

• Technical Task: Build endpoint that extracts subtopics and related concepts from input

Day 13: AI Model Abstraction Layer

• Theory: Vendor-agnostic AI integration design

• Coding Exercise: Implement adapter pattern for multiple AI providers

• Technical Task: Create abstraction layer that works with different AI service providers

Day 14: AI Service Testing Framework

• Theory: Testing strategies for AI-powered services

• Coding Exercise: Build automated testing framework for AI-generated content

• Technical Task: Implement unit and integration tests for the AI services

Week 3: Core Business Logic

Day 15: Question Difficulty Classification

• Theory: Computational approaches to difficulty assessment

• Coding Exercise: Implement difficulty classification algorithm

• Technical Task: Create service that analyzes and assigns difficulty levels to questions

Day 16: Progressive Difficulty Algorithm - Design

• Theory: Adaptive learning algorithms and difficulty progression

• Coding Exercise: Design progressive difficulty algorithm with clear rules

• Technical Task: Document algorithm with flowcharts and pseudocode

Day 17: Progressive Difficulty Algorithm - Implementation

• Theory: Algorithm implementation and performance considerations

• Coding Exercise: Implement progressive difficulty service

• Technical Task: Create endpoint that returns questions in difficulty sequence

Day 18: Quiz Scoring Engine

• Theory: Scoring algorithms and normalization techniques

• Coding Exercise: Implement comprehensive scoring system with weighting

• Technical Task: Build scoring service with different scoring strategies

Day 19: Performance Analytics Engine

• Theory: Educational analytics and performance metrics

• Coding Exercise: Implement analytics processing service

• Technical Task: Create data aggregation endpoints for user performance

Day 20: Topic Relationship Mapping

• Theory: Knowledge graphs and relationship modeling

• Coding Exercise: Design and implement topic relationship service

• Technical Task: Build API that returns related topics with relationship types

Day 21: Learning Path Generator

• Theory: Curriculum sequencing and learning path algorithms

• Coding Exercise: Implement learning path generation service

• Technical Task: Create endpoint that returns optimized topic sequence

Week 4: Advanced Backend Features

Day 22: Caching Strategy Implementation

• Theory: Caching patterns and invalidation strategies

• Coding Exercise: Design and implement caching layer for quiz content

• Technical Task: Add Redis caching to high-traffic endpoints with proper TTL

Day 23: Rate Limiting and Request Throttling

• Theory: API protection and resource management

• Coding Exercise: Implement rate limiting middleware

• Technical Task: Add tiered rate limits for different API endpoints

Day 24: Logging and Monitoring Service

• Theory: Application observability and log management

• Coding Exercise: Implement structured logging system

• Technical Task: Add comprehensive logging to all services with context

Day 25: Error Handling Framework

• Theory: Robust error handling patterns and error normalization

• Coding Exercise: Design and implement error handling framework

• Technical Task: Add global error handler with proper response formatting

Day 26: Background Job Processing

• Theory: Asynchronous job processing and scheduling

• Coding Exercise: Implement job queue for long-running tasks

• Technical Task: Create worker service for processing content generation jobs

Day 27: Notification Service

• Theory: Event-driven architecture and notification patterns

• Coding Exercise: Design and implement notification service

• Technical Task: Create endpoints for managing notification preferences and delivery

Day 28: Data Export Service

• Theory: Data serialization and export formats

• Coding Exercise: Implement configurable data export service

• Technical Task: Create endpoints for exporting quiz results in multiple formats

Week 5: API Integration and Testing

Day 29: API Documentation

• Theory: API documentation standards and tools

• Coding Exercise: Implement OpenAPI specification for all endpoints

• Technical Task: Generate interactive API documentation with Swagger

Day 30: API Versioning Strategy

• Theory: API versioning approaches and backward compatibility

• Coding Exercise: Implement API versioning system

• Technical Task: Refactor endpoints to support multiple versions

Day 31: Unit Testing - Services

• Theory: Unit testing principles and mocking

• Coding Exercise: Write comprehensive unit tests for business logic

• Technical Task: Achieve 80% test coverage for core services

Day 32: Integration Testing - API

• Theory: Integration testing strategies

• Coding Exercise: Create integration test suite for API endpoints

• Technical Task: Implement automated test pipeline for API validation

Day 33: Load Testing and Performance

• Theory: Load testing methodologies and tools

• Coding Exercise: Design and implement load testing scripts

• Technical Task: Conduct load tests and optimize bottlenecks

Day 34: Security Testing

• Theory: API security testing and vulnerability assessment

• Coding Exercise: Implement security tests for authentication and authorization

• Technical Task: Conduct security audit and fix identified issues

Day 35: End-to-End Testing

• Theory: E2E testing approaches for backend systems

• Coding Exercise: Create end-to-end test scenarios

• Technical Task: Implement automated E2E tests for critical flows

Week 6: DevOps and Infrastructure

Day 36: Environment Configuration

• Theory: Environment management and configuration

• Coding Exercise: Implement environment-based configuration system

• Technical Task: Create development, testing, and production configurations

Day 37: Containerization with Docker

• Theory: Container principles and implementation

• Coding Exercise: Create Dockerfiles for all services

• Technical Task: Build and test Docker images for application components

Day 38: Docker Compose Setup

• Theory: Multi-container applications with Docker Compose

• Coding Exercise: Create Docker Compose configuration

• Technical Task: Run complete application stack with Docker Compose

Day 39: CI Pipeline with GitHub Actions

• Theory: Continuous Integration principles and implementation

• Coding Exercise: Create CI workflow configuration

• Technical Task: Set up automated build and test pipeline

Day 40: CD Pipeline for Backend Services

• Theory: Continuous Deployment strategies

• Coding Exercise: Create CD workflow configuration

• Technical Task: Implement automated deployment for backend services

Day 41: Database Backup and Recovery

• Theory: Data backup strategies and disaster recovery

• Coding Exercise: Implement database backup scripts

• Technical Task: Create automated backup and recovery system

Day 42: Monitoring and Alerting

• Theory: Application monitoring and alerting systems

• Coding Exercise: Set up monitoring for backend services

• Technical Task: Implement alerting for critical service metrics

Week 7: Minimal Frontend and Integration

Day 43: API Integration Layer

• Theory: Frontend-backend integration patterns

• Coding Exercise: Create API client library with proper error handling

• Technical Task: Implement API integration layer for frontend

Day 44: User Authentication Flow

• Theory: Authentication flow in frontend applications

• Coding Exercise: Implement authentication components

• Technical Task: Create login and registration pages with validation

Day 45: Quiz Management Interface

• Theory: CRUD operations in frontend applications

• Coding Exercise: Implement quiz management components

• Technical Task: Create quiz creation and management pages

Day 46: Quiz Taking Interface

• Theory: Interactive quiz interfaces and state management

• Coding Exercise: Implement quiz session components

• Technical Task: Create question presentation and submission flow

Day 47: Results and Analytics Interface

• Theory: Data visualization for educational applications

• Coding Exercise: Implement analytics dashboard components

• Technical Task: Create performance visualization pages

Day 48: Error Handling and Loading States

• Theory: User experience for asynchronous operations

• Coding Exercise: Implement error boundary and loading components

• Technical Task: Add error handling and loading states to all pages

Day 49: End-to-End Integration

• Theory: Full stack integration strategies

• Coding Exercise: Complete frontend-backend integration

• Technical Task: Test and fix integration issues

Week 8: Performance Optimization and Advanced Features

Day 50: Database Query Optimization

• Theory: Database performance tuning techniques

• Coding Exercise: Analyze and optimize database queries

• Technical Task: Implement database indexing and query refactoring

Day 51: API Response Optimization

• Theory: API performance optimization strategies

• Coding Exercise: Implement response compression and optimization

• Technical Task: Measure and improve API response times

Day 52: Memory Management Optimization

• Theory: Server memory optimization techniques

• Coding Exercise: Analyze and fix memory usage issues

• Technical Task: Implement memory profiling and optimization

Day 53: Connection Pooling and Resource Management

• Theory: Connection management and resource utilization

• Coding Exercise: Implement connection pooling for database and external services

• Technical Task: Configure and optimize resource limits

Day 54: Multi-Model Quiz Generation

• Theory: Hybrid AI model approach for content generation

• Coding Exercise: Implement multi-model generation strategy

• Technical Task: Create service that uses different models for different question types

Day 55: Content Curation Workflow

• Theory: Human-in-the-loop systems for content quality

• Coding Exercise: Implement content curation workflow

• Technical Task: Create admin interface for content review and approval

Day 56: Automated Content Refreshing

• Theory: Content lifecycle management strategies

• Coding Exercise: Implement automated content refresh service

• Technical Task: Create scheduled jobs for content updates

Week 9: Final Integration and Deployment

Day 57: Production Environment Setup

• Theory: Production deployment architecture

• Coding Exercise: Configure production environment

• Technical Task: Set up production infrastructure with scaling

Day 58: Final Security Audit

• Theory: Comprehensive security audit process

• Coding Exercise: Conduct security testing and fixes

• Technical Task: Implement security recommendations

Day 59: Documentation Finalization

• Theory: System documentation best practices

• Coding Exercise: Create comprehensive API and system documentation

• Technical Task: Document deployment and maintenance procedures

Day 60: Final Deployment and Project Review

• Theory: Production deployment checklist

• Coding Exercise: Execute production deployment

• Technical Task: Conduct post-deployment verification and testing

Technical Stack

Backend Focus:

1. Core Backend: Node.js with Express or NestJS

2. Database: MongoDB with Mongoose

3. AI Integration: OpenAI API with custom abstraction layer

4. Authentication: JWT-based authentication

5. Testing: Jest, Supertest for API testing

6. DevOps: Docker, GitHub Actions

7. Monitoring: Winston/Pino for logging, Prometheus for metrics

Minimal Frontend:

1. Framework: React with minimal setup

2. State Management: React Context or Redux

3. API Integration: Axios with custom client

Daily Workflow

Each day should follow this structured workflow:

1. Morning: Study theory and plan implementation (1 hour)

2. Development: Implement the day's coding exercise (2-3 hours)

3. Testing: Write tests and verify functionality (1 hour)

4. Documentation: Document what you've built and learned (30 minutes)

5. Review: Commit code with proper messages and review the day's work (30 minutes)

Implementation Guidelines

1. Follow SDLC Principles:

   • Document requirements before coding

   • Design before implementation

   • Test thoroughly after coding

   • Review and refactor regularly

2. Source Control Best Practices:

   • Create feature branches for each day's work

   • Write meaningful commit messages

   • Use pull requests for major features

   • Review code before merging

3. Code Quality Standards:

   • Follow consistent coding standards

   • Write clear comments and documentation

   • Create reusable and modular code

   • Implement proper error handling

4. Testing Strategy:

   • Write unit tests for all business logic

   • Create integration tests for API endpoints

   • Implement end-to-end tests for critical flows

   • Automate testing in CI pipeline

This comprehensive curriculum balances theoretical knowledge with intensive hands-on practice, focusing on backend development and business logic implementation. By following this day-by-day plan, you'll gain practical experience with the entire software development lifecycle while building a sophisticated AI-powered quiz platform.