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Distributed Systems
in 5 Days

CAP theorem, consensus algorithms, replication strategies, sharding, and eventual consistency — the concepts behind every scalable system.

5 lessons
Self-paced
~60 min/day
Free forever
No account needed
Start Day 1 — Free → See what's covered
What you'll learn

Distributed Systems in 5 Days

Free 5-day distributed systems course. CAP theorem, consensus, replication, sharding, and eventual consistency.

  • Apply CAP theorem to real architecture decisions
  • Explain Paxos and Raft consensus algorithms
  • Design leader-follower and multi-master replication
  • Choose appropriate sharding strategies
  • Reason about eventual consistency and conflict resolution
  • Handle partial failures and network partitions gracefully
CAP
theorem
Raft
consensus
5
lessons
$0
cost
5-Day Curriculum

Every lesson has a real exercise.
No theory without practice.

01
CAP Theorem & Consistency
CAP theorem, PACELC, consistency models from linearizable to eventual
CAPlinearizabilityPACELC
→
02
Consensus Algorithms
Paxos basics, Raft leader election, log replication, safety guarantees
RaftPaxosleader election
→
03
Replication
Sync vs async replication, leader-follower, multi-leader, CRDTs
replicationmulti-leaderCRDTs
→
04
Sharding & Partitioning
Hash vs range partitioning, consistent hashing, hot spots, rebalancing
consistent hashinghot spotsrebalancing
→
05
Failure Handling
Failure detection, circuit breakers, timeouts, sagas, idempotency
circuit breakersagaidempotency
→
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Your instructor
B
Bo Peng
Founder, Precision AI Academy

Kaggle Top 200 data scientist. Trained 400+ professionals across universities and federal agencies. Built production systems at scale. This course is practical first — every lesson has working examples and an exercise you can finish in under an hour.

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