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system Advanced 21 lessons

Distributed Algorithms

Solve the hardest problems in computing. Master Consensus, Paxos, Raft, and Logical Clocks to build fault-tolerant distributed systems.

Distributed systems are notoriously difficult. This course covers the theoretical algorithms that keep the internet running. You will understand the challenge of consensus in unreliable networks. Master Logical Clocks (Lamport, Vector) for ordering events, and deep dive into Leader Election algorithms like Paxos and Raft. We cover Distributed Hash Tables (DHTs) and Gossip protocols. This is heavy on theory and logic, essential for architects designing cloud-native databases and services.

✅ 100% Free & Lifetime Access
⏱️ 5-Minute Lessons (Bite-sized learning)
🚀 21-Lesson Path (Independent modules)
📱 Mobile Friendly (Learn anywhere)
CS PhDs
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Secure Enrollment via SSL

Complete Course Syllabus

  • 1
    Time & Order
    Physical clocks vs Logical clocks and causality.
  • 2
    Consensus Problem
    The Two Generals problem and Byzantine faults.
  • 3
    Raft Algorithm
    Leader election and log replication step-by-step.
  • 4
    Paxos Explained
    The classic (and hard) consensus protocol deconstructed.
  • 5
    Gossip Protocols
    Epidemic algorithms for eventual consistency.

Estimated completion time: 21 lessons • Self-paced learning • Lifetime access

Career Outlook

Estimated Salary
$150k - $220k

Career Paths

Distributed Systems Eng $160k-$230k
Database Architect $150k-$210k
Principal Engineer $180k-$250k

What You Will Learn

Implement Consensus algorithms like Raft and Paxos
Order distributed events using Lamport and Vector clocks
Design fault-tolerant systems that survive node failures
Understand Consistency models (Strong, Eventual, Causal)
Analyze distributed system correctness and safety

Skills You Will Gain

Distributed Theory Consensus Algorithms Fault Tolerance Logic & Proofs System Design

Who Is This For

Dist Systems Engs
Database Architects
Researchers

Prerequisites

Algorithms
Discrete Math

Distributed Algorithms FAQs

Theory?

Yes, heavy algorithmic theory and logic.

Coding?

We implement simplified versions (e.g., in Go).

Why learn?

To build systems like Kubernetes, Kafka, or Etcd.

Prereqs?

Strong CS fundamentals and algorithmic thinking.

Need more info?
All Reork courses are 100% free, self-paced, and fully accessible on mobile devices. No prior experience is required. Read our full Platform FAQ.

Tech Stack & Tools

Whiteboard
TLA+ (Intro)
Go (for implementation)

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