The fastest path from beginner to expert in IT is to master durable fundamentals, build deployable projects with tests and documentation, and iterate through cloud, security, and reliability practices until your portfolio mirrors production standards. Use focused sprints, measurable outcomes, and multi‑artifact proof (code, docs, demos) at each stage to compound skills.
Stage 0: Digital foundations (1–2 weeks)
- Set up a stable environment: password manager, MFA, backups, terminal, Git, code editor, and a clean project template with README, tests, CI, and Docker.
- Learn file systems, shell basics, HTTP/HTTPS, and browser tools; practice troubleshooting with logs, process lists, and network utilities.
Stage 1: Programming fundamentals (4–6 weeks)
- Pick one primary language (Python, Java, Go, or TypeScript) and cover control flow, data structures, functions, OOP, error handling, and testing.
- Build two small utilities and one CLI; write unit tests, add a linter/formatter, and publish with a one‑command run script.
Stage 2: Core CS essentials (6–8 weeks)
- Algorithms and data structures: arrays, hash maps, stacks/queues, trees/graphs, recursion, sorting, greedy, and basic DP with time/space analysis.
- Systems basics: OS processes/threads, memory, files, and concurrency; networking basics with sockets/HTTP and REST semantics.
Stage 3: Databases and SQL (3–4 weeks)
- Relational modeling, normalization, indexing, transactions, and query tuning; practice complex joins and window functions.
- Add a small project with migrations and a performance note (EXPLAIN plans and before/after latency).
Stage 4: Web and APIs (4–6 weeks)
- Build a REST or GraphQL service: auth, pagination, validation, rate limiting, and error models; document with OpenAPI and add integration tests.
- Frontend basics: accessibility, forms, and performance budgets; deliver a minimal UI that consumes your API.
Stage 5: Cloud and DevOps (6–8 weeks)
- Containerization and compose/devcontainers for parity; CI/CD with tests, security scans, and artifact signing.
- Provision a minimal stack with IaC on a free tier; add metrics/logs/traces, dashboards, and a simple SLO with an alert.
Stage 6: Security by default (3–4 weeks)
- Secrets management, least privilege IAM, parameterized queries, dependency/SBOM scans, and image signing; add a threat model to each repo.
- Run a mini incident drill: rotate a test credential, verify logs and alerts, and write a short postmortem.
Stage 7: Data/ML or specialization (6–8 weeks)
- Data/ML track: SQL + pandas, feature engineering, model evaluation, and a model card; deploy a small inference endpoint with monitoring.
- Alternative tracks: pick one—SRE/platform (Kubernetes + GitOps), cybersecurity (detections + cloud guardrails), or frontend excellence (a11y + e2e tests).
Stage 8: System design and reliability (4–6 weeks)
- Practice requirements → data model → APIs → scaling: caching, queues, idempotency, backpressure, and rollout/rollback plans.
- Load‑test a feature, document bottlenecks, and publish a case study with p95 latency and error‑rate improvements.
Portfolio that proves expertise
- 3–5 polished repos with tests, CI badges, Docker, and one‑command setup; each includes a README, design doc/ADR, and a 3–5 minute demo.
- At least one cloud‑deployed service with IaC, observability dashboards, an SLO, and a documented failure drill/postmortem.
Certifications that help (paired with projects)
- One associate cloud cert for fundamentals; optionally add security or data certs; always link badges to live repos and demos that apply the concepts.
- Prefer microcredentials that map to portfolio work (e.g., Terraform, Kubernetes basics, or SQL performance).
Weekly operating rhythm
- Plan: choose 2–3 outcomes; time‑box two 90‑minute deep‑work blocks and one review slot.
- Build: ship a feature with tests and docs; record a short demo; log metrics before/after.
- Reflect: write a brief note on lessons, pitfalls, and what to improve next week.
Interview‑readiness layering
- Coding: daily problem at target difficulty; emphasize clarity, tests, and complexity narration.
- Design: one mini system design per week using a template (requirements → models → APIs → scaling → reliability).
- Behavioral: three 90‑second stories with metrics (bug you crushed, performance win, cross‑team delivery).
12‑month roadmap (example)
- Q1: Language + CS + SQL; build a CLI and a basic API; add tests/CI and Docker; publish two demos.
- Q2: Cloud + IaC + observability; deploy your API; add a simple frontend; write ADRs and a postmortem from a small failure.
- Q3: Specialize (data/ML, SRE, security, or frontend); complete a capstone with measurable outcomes; contribute to OSS.
- Q4: Harden security and reliability; obtain one role‑aligned certification; conduct mock interviews and apply with your portfolio links.
Common pitfalls and guardrails
- Tutorial hopping: require a shipped feature and demo per topic before moving on.
- Ignoring tests and docs: block merges without tests and a minimal README; add CI status badges.
- Over‑relying on AI: write tests first, validate outputs, and document where AI assisted with a short validation note.
Following this roadmap—with disciplined weekly execution, measurable outcomes, and production‑minded artifacts—will take you from beginner to expert while creating a portfolio that convinces employers you can deliver on day one.