Code Labs Academy

Want real cybersecurity practice without breaking rules or your budget? Build a beginner home lab with virtual machines, safe targets, and 3 portfolio projects you can share.

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Stuck on SQL interview follow-ups like "now do it per customer"? Learn SQL window functions with real examples: ROW_NUMBER, LAG/LEAD, running totals, rolling averages.

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New on Code Labs Academy: cloud-aware U‑Net flood mapping from Sentinel‑2 in Python. Learn band choices, masked losses, IoU/Dice evaluation, and how to turn flood extent into risk-ready GIS layers.

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Building demand response controllers? This deep dive shows how to design an MDP, shape rewards for cost/comfort/carbon, and train stable DQN + actor–critic agents in PyTorch.

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Stop re-googling pandas basics. Our beginner pandas cheat sheet breaks down 30 commands you’ll use weekly (filter, groupby, merge, pivot, export) with copy-ready examples.

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Basic ML is step one. If your model works in a notebook but breaks in the real world, you need MLOps: reproducible training, deployment basics, CI/CD, and monitoring.

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Your GitHub portfolio is judged fast. Pin 3-6 flagship repos, write READMEs that run, add a few tests, and hide tutorial clutter + secrets.

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Building React projects but not getting interviews? Pick projects that prove skills: state, APIs, forms, and deployment. Our guide lists 12 ideas and what each one signals to hiring teams.

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Build a Node.js REST API with JWT auth + Postgres, step by step. Includes a 3 to 4 week roadmap, security checklist, and portfolio tips for career changers.

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Portfolio tip: build JavaScript DOM projects that behave like real products: state, accessibility, loading/error UI. We shared 7 hiring-manager-friendly ideas (to-do, product finder, form wizard, mini SPA, more).

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React or Angular in 2026? Pick the one that matches your first job target and portfolio plan. We wrote a beginner-friendly guide focused on the learning curve, projects, and interviews.

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LLM summaries can save time in EHR workflows, but hallucinations can introduce clinical risk.
This guide shows claim-level evaluation and risk-weighted safety metrics so high-impact errors don’t slip through.

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Small clinical datasets make privacy a first‑order constraint. New guide: DP‑SGD with PyTorch + Opacus, tuning clipping (C) and noise (σ), tracking (ε, δ), and plotting AUROC vs ε.

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Deploying healthcare ML? The hard part starts after release: drift, calibration shifts, API abuse, and PHI leaks via logging. Our new guide shows what to monitor and how to respond.

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Switching careers into UX/UI? Stop guessing. Our guide lays out a realistic bootcamp timeline, what to include in 2-3 portfolio case studies, and a first-job plan you can repeat weekly.

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Clinical AI can look great on ROC AUC and still hurt patients and teams. We explain cost‑sensitive metrics, calibration, and decision curves so your evaluation matches real clinical utility.

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Build a portfolio that aligns with the role: UX Designer vs. Product Designer. Learn who owns research, flows, UI craft, and outcomes, plus what to show in each case study. Which role are you targeting?

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Cybersecurity or software engineering? If you’re switching into tech, the right choice depends on what you enjoy: investigating risk vs building features.

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New on the Code Labs Academy blog: handling non‑IID clinical data in federated learning. FedAvg vs FedProx, client‑drift pitfalls, and practical personalization with PyTorch examples.

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ΔΥΠΑ (ex-OAED) vouchers + EU programs can cut the cost of upskilling in Greece. But how do you turn training into a real tech pathway? Our guide breaks down eligibility, certification, and how to stack learning into a portfolio.

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Shipping a clinical ML model as an API? Treat it like patient access, not just a microservice.

Our new guide shows zero‑trust patterns (OAuth2/OIDC, mTLS, audit logs) in FastAPI.

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Working with EHR data? k-anonymity and differential privacy solve different privacy problems. We break down the math, show Python demos of re-identification risk, and share a practical decision framework.

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Working with EHR data? k-anonymity and differential privacy solve different privacy problems. We break down the math, show Python demos of re-identification risk, and share a practical decision framework.

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Working full-time but want to switch into tech? Our 2026 guide breaks down part-time online bootcamp schedules, weekly workload, and outcomes that matter (projects, portfolio, career support).

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Coding assistants can help you move faster in a bootcamp, but they don’t replace fundamentals. In 2026, the learners who win can debug, test, and explain their choices.

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Bootcamp interview soon? In 2026, admissions teams care less about perfect code and more about your goals, time plan, and learning habits. Our guide breaks down the questions and how to answer them.

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Madrid, Barcelona, or remote? Choosing a coding bootcamp in Spain for 2026 is easier with a simple checklist for curriculum, projects, and career support.
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HIPAA-aware de‑identification for clinical notes isn’t just regex. Build a layered Python pipeline: pattern detectors + PHI tagging + audit-friendly redaction spans, with notes on DP‑SGD when models are shared.

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Marketing, HR, and ops teams are being asked to deliver more with the same headcount. Our 2026 guide shows practical workflows, risk checks, and a 30-60-90 plan to build credibility fast.

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Annual awareness isn’t cybersecurity training for employees. UK teams cut risk faster with 3 layers: org-wide hygiene, role-based drills for high-risk teams, and hands-on labs for IT & engineers.

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