Find a chapter, lesson or practice exerciseSUPPORTING MATERIAL
REFERENCE SHELF
Your guided curriculum
SUPPORTING MATERIALGUIDED READING

Find a chapter, lesson or practice exercise

Part A · Coding and problem solving

Index Chapter What you learn
CH 01 Data structures and algorithms Learn the shared structures, operations, costs, and algorithm patterns before practice.
CH 02 Coding problems and trade-offs Solve a clear problem, verify its examples, and defend the solution under follow-ups.
CH 03 AI-assisted code changes Clarify a requirement, make a bounded change, and verify the result.

Part B · Production applications

Index Chapter What you learn
CH 04 APIs and background work Trace a request, define its contract, and coordinate bounded work.
CH 05 Data models and transactions Model authoritative data, explain a query plan, and protect concurrent writes.
CH 06 Frontend state and API integration Preserve user intent across browser, API, and persisted state.
CH 07 Testing and debugging Reproduce a defect, build a check that catches it, and assess a proposed repair.
CH 08 Identity and authorization Enforce identity, ownership, and trust boundaries beyond the interface.

Part C · System design and scale

Index Chapter What you learn
CH 09 System design under constraints Turn requirements and workload estimates into an explainable architecture.
CH 10 Data systems at scale Reason about caches, replication, partitioning, streams, and coordination scope.
CH 11 Capacity, performance and cost Measure the bottleneck and defend an improvement with resource and cost evidence.

Part D · Production operations

Index Chapter What you learn
CH 12 AWS infrastructure Map a mechanism to explicit infrastructure, permissions, and operational limits.
CH 13 Delivery and controlled rollouts Build once, verify compatibility, and release a change with stop conditions.
CH 14 Production observability Use logs, metrics, and traces to answer a concrete system question.
CH 15 Reliability and incident recovery Budget failures, bound overload, and recover from evidence.

Part E · System evolution and leadership

Index Chapter What you learn
CH 16 Live migrations Move live data and clients through compatibility, reconciliation, rollback, and retirement.
CH 17 Technical decisions and engineering effectiveness Make options, ownership, adoption, and cross-team decisions explicit.

Optional specialization · AI systems

Index Chapter What you learn
CH 18 AI evaluation and guardrails Evaluate an AI feature, protect permissions, and enforce quality and task budgets.

Turn a lesson into an observable result

  1. Read the application background and trace one concrete input to its result.
  2. Predict the initial diagram, then try the baseline.
  3. Carry out the assignment. Use the supplied reference to compare your result.
  4. Work through a changed requirement. Explain the new failure and update the implementation or diagram.
  5. Use the tests or acceptance checks, then take an unfamiliar assessment.
  6. Return to later-topic follow-ups after their prerequisites. Record the gap rather than treating a job title as a reading route.

AI-assisted exercises practice specification and review. Independent exercises practice implementation and explanation. Both use the same concepts and pages. Follow the stated tool rules for each assessment.