Hands-on Twitter System Design Course

Build Production-Ready Social Media Architecture From Scratch

Course Details

Why This Course?

Most system design courses teach you to draw boxes on whiteboards. This course teaches you to build systems that actually work. While others focus on theoretical concepts, you'll construct a complete Twitter-like platform handling millions of users, experiencing real bottlenecks and implementing proven solutions.

The Reality Gap: Fresh graduates can explain CAP theorem but struggle when their first production system crashes under 1,000 concurrent users. Senior engineers know their local patterns but freeze when designing global distribution. This course bridges that gap through progressive complexity - you'll start with 1,000 users and scale to 10 million, experiencing every architectural decision point.

Career Acceleration: System design expertise separates senior engineers from architects. Companies like Netflix, Uber, and Airbnb pay $200K+ premiums for engineers who understand distributed systems at scale. This course provides that expertise through hands-on implementation, not theoretical knowledge.

Production Experience Without Risk: Learn from 20+ years of hyperscale failures and optimizations compressed into practical exercises. You'll implement the exact patterns used by Twitter, Instagram, and TikTok without waiting years to encounter these challenges.

What You'll Build

Week 1: Core Twitter MVP

• Real-time tweet posting and timeline generation (1K users)

• Database schema optimized for social media patterns

• Basic caching layer with Redis

• Message queue system for event processing

• Performance monitoring dashboard

Week 2: Regional Scale System

• Multi-region deployment across 3 continents (100K users)

• Database sharding with consistent hashing

• Advanced load balancing with failover

• Cross-region data synchronization

• Content delivery network integration

Week 3: Production Hyperscale

• Real-time recommendation engine (1M users)

• Content moderation with ML integration

• Celebrity user handling architecture

• Search infrastructure for billions of tweets

• Chaos engineering framework

Week 4: Advanced Optimization

• Mathematical performance modeling

• Statistical A/B testing for infrastructure

• Advanced consensus algorithms

• Failure prediction systems

• Cost optimization achieving 30% savings

Week 5: Production Operations

• Complete monitoring and alerting systems (10M users)

• Automated deployment pipelines

• Disaster recovery with 15-minute RTO

• SRE practices and incident response

• Capacity planning and resource management

Final Deliverable: Production-ready Twitter clone with complete documentation, operational runbooks, and architectural defense presentation.

Who Should Take This Course?

Primary Audience:

• Fresh CS Graduates: Bridge the gap between academic knowledge and production systems

• Software Engineers (1-5 years): Advance from feature development to architectural thinking

• Senior Engineers: Gain distributed systems expertise for Staff/Principal roles

• Software Architects: Add hyperscale patterns and mathematical optimization

Secondary Audience:

• Product Managers: Understand technical constraints for better product decisions

• UI/UX Designers: Learn backend limitations affecting user experience design

• QA Engineers: Master testing strategies for distributed systems

• DevOps/SRE: Gain deep application architecture understanding

Specialized Value:

• Data Engineers: Apply real-time processing patterns to data pipelines

• Engineering Managers: Develop technical depth for architectural discussions

• Technical Writers: Understand complex systems for better documentation

• IT Consultants: Gain expertise for enterprise client engagements

What Makes This Course Different?

Code-First Learning: Every concept includes working implementation. No abstract diagrams without corresponding code. You'll debug real performance issues and implement actual solutions.

Progressive Complexity: Each week increases system scale by 10x, mimicking natural growth patterns. You'll experience the exact decision points that force architectural evolution in production systems.

Mathematical Foundations: Unlike courses relying on rules of thumb, you'll learn queuing theory for capacity planning, statistical methods for optimization, and failure mathematics for reliability engineering.

Production-Hardened Patterns: Every solution comes from real systems at companies like Netflix (chaos engineering), Google (global distribution), LinkedIn (social media scaling), and Amazon (distributed databases).

Visual-First Understanding: Complex concepts become intuitive through interactive diagrams, real-time monitoring visualizations, and failure scenario animations.

Immediate Application: Every lesson produces artifacts you can use in current projects. Students report immediate impact on their work within days of each session.

Industry Mentorship: Direct access to senior engineers from FAANG companies who've built these systems in production.

Key Topics Covered

Real-Time Data Architecture

• Event-driven microservices with guaranteed delivery

• Stream processing for social media feeds

• WebSocket management for millions of connections

• Real-time recommendation engines

Database Scaling Patterns

• Social media schema design and optimization

• Sharding strategies for user-generated content

• Cross-shard query patterns for timelines

• Replication with consistency guarantees

Global Distribution

• Multi-region deployment strategies

• Content delivery for dynamic social content

• Cross-region synchronization with conflict resolution

• Latency optimization for global users

Performance Engineering

• Caching hierarchies for social media workloads

• Load balancing with consistent hashing

• Auto-scaling based on mathematical models

• Performance monitoring and optimization

Production Reliability

• Failure detection and prevention systems

• Chaos engineering for systematic testing

• Disaster recovery with automated procedures

• SRE practices adapted for social media

Cost Optimization

• Resource utilization analysis and improvement

• Cloud cost modeling and reduction strategies

• Capacity planning with statistical methods

• Performance per dollar optimization

Prerequisites

Technical Foundation (Required):

• Programming Experience: 6+ months in any language (Java, Python, Go, JavaScript)

• Database Basics: SQL queries, indexes, primary/foreign keys

• Web Development: HTTP, REST APIs, JSON handling

• Command Line: Basic terminal commands and file operations

Distributed Systems (Helpful):

• Basic Cloud Knowledge: Understanding of virtual machines and load balancers

• Caching Concepts: Awareness of Redis or Memcached use cases

• Message Queues: Exposure to asynchronous processing concepts

Mathematical Comfort (Beneficial):

• High School Statistics: Understanding averages, percentiles, distributions

• Graph Reading: Interpreting performance charts and system metrics

• Basic Algebra: Comfortable with equations and optimization

Professional Context (Essential):

• Growth Mindset: Willingness to tackle complex technical challenges

• Time Commitment: 10-12 hours per week for hands-on exercises

• Development Environment: Modern laptop with reliable internet

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Course Structure

Format: 5-week intensive program with daily hands-on exercises Time Commitment: 10-12 hours per week (2 hours daily) Class Size: Maximum 25 students for personalized attention Delivery: Live sessions + recorded content + hands-on labs Assessment: Progressive project building + peer code reviews

Daily Structure:

• Morning Session (45 min): Core concept introduction with visual explanations

• Implementation Lab (60 min): Hands-on coding and system building

• Troubleshooting (15 min): Debug common issues and optimization techniques

Weekly Progression:

• Each week multiplies system complexity by 10x

• Previous week's system serves as foundation for next level

• Continuous integration ensures working system at each stage