Introduction to Distributed Systems for Dummies Course Syllabus

Overview: This course provides a comprehensive, code-free introduction to distributed systems, combining core theoretical concepts with real-world case studies. Designed for beginners, it spans approximately 10 hours of interactive learning across eight modules, culminating in a final quiz and certificate of completion. You'll build foundational knowledge essential for system design and backend engineering roles.

Module 1: What is a Distributed System?

Estimated time: 1 hour

• Definitions and characteristics of distributed systems
• Motivations for using distributed systems
• Real-world examples and use cases
• Interactive quiz on system properties

Module 2: Achieving Resilience & Scalability

Estimated time: 2.5 hours

• Fault tolerance and handling hardware failures
• Software failure management and reliability
• Availability and load balancing techniques
• Maintainability in large-scale systems

Module 3: Data Strategies in Distributed Architectures

Estimated time: 3 hours

• Data replication methods and trade-offs
• Partitioning strategies including consistent hashing
• Tunable consistency models
• Caching strategies and cache eviction policies

Module 4: Inter-Node Communication

Estimated time: 1 hour

• Database-based inter-node coordination
• Synchronous and asynchronous messaging
• Microservices communication patterns

Module 5: Large‑Scale Data Processing

Estimated time: 1 hour

• Batch and stream processing fundamentals
• MapReduce paradigm
• Cloud-scale data workflows

Module 6: Architectural Pattern Deep Dive

Estimated time: 1 hour

• Replication services and sharding
• Lambda architecture components
• Command Query Responsibility Segregation (CQRS)

Module 7: Case Study – Apache Spark

Estimated time: 0.75 hours

• Apache Spark basics
• Architecture for distributed analytics
• Spark cluster design scenarios

Module 8: Case Study – Apache Druid

Estimated time: 0.75 hours

• OLAP vs OLTP workloads
• Druid architecture overview
• Data ingestion and querying in Druid

Prerequisites

• Familiarity with basic computer science concepts
• Understanding of fundamental networking principles
• Basic knowledge of databases and client-server architecture

What You'll Be Able to Do After

• Explain core distributed systems concepts clearly
• Analyze trade-offs in scalability, availability, and consistency
• Apply data replication and partitioning strategies effectively
• Understand communication patterns in microservices and distributed databases
• Interpret real-world architectures like Spark and Druid