Engineering / foundation
Understand the machine
Trace data and work through programs, memory, networks, storage, and running services.
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Module 01 foundation
Understand the machine
Trace data and work through programs, memory, networks, storage, and running services.
- 01
Bits, numbers, and the cost of approximation
Connect binary representation, rounding, tensor precision, and numerical error before choosing a data type.
15 min - 02
Algorithms: count the work before buying capacity
Reason about correctness, growth rates, and the difference between an asymptotic bound and a latency measurement.
16 min - 03
Memory, locality, and the shape of data
Estimate payloads, distinguish virtual from physical memory, and understand why access patterns affect throughput.
16 min - 04
Concurrency without confusing it with parallelism
Build a mental model of processes, shared state, queues, and the limits of adding workers.
17 min - 05
Networks and HTTP: follow a request end to end
Separate protocol semantics, transfer time, round trips, and deadlines in a realistic request journey.
16 min - 06
API contracts that survive imperfect clients
Design explicit inputs, outputs, errors, compatibility rules, and duplicate handling across service boundaries.
16 min - 07
Data, storage, and the meaning of a committed write
Connect schemas, constraints, transactions, indexes, retention, and recovery to the promises an application makes.
17 min - 08
Tests as evidence, reproducibility as a method
Build checks around behavior and invariants, then record enough context to reproduce a result.
17 min - 09
From source code to a controlled release
Separate builds, artifacts, configuration, migrations, and rollout decisions so a change can be verified and recovered.
17 min - 10
Observability: turn a symptom into a testable explanation
Use metrics, logs, traces, latency distributions, and disciplined hypotheses to debug systems without guessing.
18 min