Phase 1 – Core Foundations (Linux, Networking, Git)
Phase 2 – Programming & Scripting
Phase 3 – Cloud Fundamentals (AWS-first)
Phase 4 – Containers & CI/CD
Phase 5 – Infrastructure as Code & Kubernetes
Phase 6 – Monitoring, Security & Real Projects
Phase 7 – Portfolio + Job Readiness

Total: 6–8 months (can be faster if full-time)

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🔹 PHASE 1: CORE FOUNDATIONS (Weeks 1–4)

Most DevOps beginners fail here. This phase is non-negotiable.

Week 1 – Linux Basics (Daily Hands-on)

Goals

• Understand Linux filesystem
• Move comfortably in terminal

Tasks

• Install Ubuntu (VM or WSL)
• Learn:
  • ls, cd, pwd, cp, mv, rm
  • cat, less, head, tail
  • grep, find
• Practice:
  • Create users
  • Change permissions (chmod, chown)

Deliverable
✔ Navigate Linux without Google
✔ Create and manage files & users

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Week 2 – Linux + Processes + Networking

Tasks

• Learn:
  • ps, top, htop
  • systemctl
  • kill, nohup
• Networking basics:
  • IP, DNS, ports
  • ping, curl, netstat, ss
• Install & run:
  • Nginx
  • Restart service

Deliverable
✔ Start/stop services
✔ Understand how apps listen on ports

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Week 3 – Git & GitHub (CRITICAL)

Tasks

• Learn:
  • git init, clone, add, commit
  • push, pull
  • branches & merge
• Create GitHub account
• Push your first repo

Mini Project

• Linux notes repo
• Commit daily

Deliverable
✔ Confident Git usage
✔ GitHub activity visible

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Week 4 – Basic Bash Scripting

Tasks

• Learn:
  • variables
  • conditionals (if)
  • loops
• Write scripts:
  • Disk usage alert
  • Backup a folder
  • Restart a service if down

Deliverable
✔ 3 working bash scripts in GitHub

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🔹 PHASE 2: PROGRAMMING (Weeks 5–6)

DevOps ≠ coding like a software engineer, but you must script.

Week 5 – Python for DevOps

Tasks

• Learn:
  • variables
  • lists, dicts
  • functions
• Practice:
  • Read/write files
  • Parse logs
  • Call shell commands

Mini Project

• Python script to monitor disk usage

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Week 6 – APIs & Automation

Tasks

• Learn:
  • REST APIs
  • JSON
• Use Python to:
  • Call public APIs
  • Automate system tasks

Deliverable
✔ Python automation repo

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🔹 PHASE 3: CLOUD FUNDAMENTALS (Weeks 7–10)

AWS is the industry default. Learn one cloud deeply.

Week 7 – AWS Basics

Tasks

• Create AWS Free Tier
• Learn:
  • EC2
  • IAM
  • Security Groups
• Launch EC2
• SSH into it

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Week 8 – Storage & Networking

Tasks

• Learn:
  • S3
  • VPC
  • Subnets
• Host a static website on S3

---

Week 9 – Databases & Scaling

Tasks

• Learn:
  • RDS
  • Load Balancers
  • Auto Scaling
• Connect EC2 → RDS

---

Week 10 – AWS Project

Project

• Deploy a web app:
  • EC2
  • Nginx
  • S3 for assets
  • IAM roles

Deliverable
✔ Cloud architecture diagram
✔ Deployed app URL

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🔹 PHASE 4: CONTAINERS & CI/CD (Weeks 11–14)

Week 11 – Docker

Tasks

• Learn:
  • Images
  • Containers
  • Volumes
• Dockerize:
  • Simple Python app

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Week 12 – Docker Compose

Tasks

• Multi-container app
• App + DB
• Use .env files

---

Week 13 – CI/CD

Tasks

• Learn:
  • GitHub Actions
• Build pipeline:
  • Build image
  • Run tests
  • Push to Docker Hub

---

Week 14 – CI/CD Project

Project

• On commit:
  • Run pipeline
  • Deploy container to EC2

Deliverable
✔ Automated deployment

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🔹 PHASE 5: INFRASTRUCTURE AS CODE & K8s (Weeks 15–18)

Week 15 – Terraform

Tasks

• Learn:
  • Providers
  • Resources
  • State
• Create:
  • EC2
  • Security Group

---

Week 16 – Advanced Terraform

Tasks

• Variables
• Modules
• Remote state (S3)

---

Week 17 – Kubernetes Basics

Tasks

• Learn:
  • Pods
  • Deployments
  • Services
• Use:
  • Minikube or Kind

---

Week 18 – Kubernetes Project

Project

• Deploy app to K8s
• Add:
  • Scaling
  • Rolling updates

Deliverable
✔ Kubernetes manifests in GitHub

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🔹 PHASE 6: MONITORING, SECURITY & RELIABILITY (Weeks 19–20)

Week 19 – Monitoring

Tasks

• Learn:
  • Prometheus
  • Grafana
• Monitor:
  • CPU
  • Memory

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Week 20 – Security & Best Practices

Tasks

• Secrets management
• IAM best practices
• Docker image scanning

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🔹 PHASE 7: PORTFOLIO & JOB READY (Weeks 21–24)

Build a DevOps Portfolio

Must Have

• 4–6 GitHub repos
• README with:
  • Architecture
  • Tools used
  • Screenshots
• One end-to-end DevOps project

Optional Certs

• AWS Cloud Practitioner
• AWS Solutions Architect (Associate)

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📊 WEEKLY TRACKING TEMPLATE (Use This)

Week:
Goals:
✔ Task 1
✔ Task 2
✔ Task 3
Repo link:
Notes:

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🚀 How to Succeed Faster (Truth)

• Build projects, not notes
• Push every week to GitHub
• Break things intentionally
• Learn debugging

1) Choose a stack (pick one to start)

You only need one primary stack to begin — you can learn others later.

Option A — JavaScript / TypeScript (recommended)

• Backend: Node.js + Express
• Why: huge ecosystem, easy transition to frontend, TypeScript adds safety and is in high demand.

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2) Core learning phases (what to learn and why)

Each phase lists must-learn topics and mini tasks.

Phase 0 — Foundations (Weeks 0–4)

Goals: basic programming fluency, Git, CLI, HTML/CSS basics (so you can do small full-stack demos).

• Programming fundamentals: variables, control flow, functions, arrays/objects, async (callbacks/promises/async-await).
• Tools: VS Code, Git, GitHub, terminal basics (cd, ls, mkdir, rm, curl).
• Web basics: HTTP, URL, status codes, headers, JSON, how browsers request resources.
• Mini tasks: build small scripts (e.g., weather CLI), make simple static HTML page, push code to GitHub.

Phase 1 — Backend basics & first REST API (Weeks 5–12)

Goals: write a real backend service, understand routing, middleware, and databases.

• Language deepening: advanced JS/TS (modules, types, error handling), or Python if chosen.
• Framework: Express (or Flask/Django).
• Databases: SQL basics (SELECT/INSERT/UPDATE/DELETE), PostgreSQL or MySQL.
• Authentication basics: sessions vs JWT.
• Testing basics: unit tests (Jest for JS / pytest for Python).
• Mini tasks: build a CRUD API for a “Notes” app with Postgres, Dockerize it, write tests, deploy.

Phase 2 — Production patterns (Weeks 13–20)

Goals: make your app robust, secure, and deployable; learn caching, background jobs, and CI.

• Docker + docker-compose.
• Logging & monitoring basics.
• Caching (Redis), background processing (Bull for Node, Celery for Python).
• Security basics: OWASP Top 10, input validation, password hashing, HTTPS/TLS basics.
• CI/CD: GitHub Actions or GitLab CI pipelines, automated tests.
• Mini tasks: add auth to Notes app, add background job (e.g., send emails), add Redis cache, configure CI pipeline.

Phase 3 — Scaling & architecture (Weeks 21–28)

Goals: understand system design basics and scaling patterns.

• Message brokers (RabbitMQ/Kafka) basics.
• Microservices vs monolith tradeoffs.
• API design: RESTful vs GraphQL.
• Load balancing, reverse proxies (Nginx), containers orchestration basics (Kubernetes intro).
• Mini tasks: split one service into two (e.g., Posts service + Auth service), or build a queue worker and scale it locally with docker-compose.

Phase 4 — Advanced features & polish (Weeks 29–36)

Goals: build larger projects, solidify testing and design skills.

• Observability: metrics, distributed tracing (concepts).
• Advanced DB topics: indexes, migrations, transactions, replication concepts.
• Performance tuning: profiling, query optimization.
• Mini tasks: build a small ecommerce prototype with payments mock, analytics events pipeline, and CI/CD; include tests and infra as code (Terraform basics optional).

Phase 5 — Interview prep & job hunt (Weeks 37–52)

• Algorithms & data structures: arrays, linked lists, trees, hash maps, sorting, complexity analysis (Big O).
• System design: prepare for basic to medium system design interviews (design a URL shortener, design a chat system).
• Mock interviews, resume tailoring, open-source contributions.
• Mini tasks: solve 40–100 algorithm problems (see schedule below), do 6 mock interviews.

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3) Detailed timeline (week-by-week for the first 12 weeks, then monthly)

I’ll show a weekly plan for the first 12 weeks (most critical) and monthly checkpoints afterward.

Week 1 (Day 1–7)

• Install tools: VS Code, Git, Node / Python, Postgres, Docker.
• Learn Git basics: git init, git add, git commit, git push.
• Do an intro tutorial: JS basics (variables, loops, functions) or Python basics if chosen.
• Mini: create GitHub repo and push a “hello world” script.

Week 2

• Deeper JS/TS: functions, objects, arrays, map/reduce/filter, promises – https://www.youtube.com/watch?v=Urwzk6ILvPQ
• CLI practice: use curl to call endpoints, run local servers. https://www.youtube.com/watch?v=q2sqkvXzsw8
• Mini: make a small script to fetch JSON from a public API and log results. https://www.youtube.com/watch?v=37vxWr0WgQk

Week 3

• HTTP fundamentals (GET/POST/etc), status codes, headers, JSON.
• Learn Express basics (or Flask): routing, middleware.
• Mini: simple Express server with 3 routes.

Week 4

• SQL basics: SELECT, WHERE, JOIN, INSERT, UPDATE, DELETE.
• Setup Postgres, connect from Node/Python.
• Mini: connect Express to Postgres and store simple records.

Weeks 5–8

• Build Notes API: CRUD endpoints + Postgres, input validation, basic auth (JWT).
• Add unit tests (Jest or pytest).
• Dockerize app + postgres via docker-compose.
• Deploy to free tier (Railway/Render/Heroku) — learn env vars and secrets.
• Outcome: deployed Notes app, tests, Dockerfile, GitHub repo.

Weeks 9–12

• Add features: rate limiting, email notifications (use SendGrid or mock), file uploads.
• Add Redis for caching.
• Add CI: run tests on PR with GitHub Actions.
• Start small frontend (optional): simple HTML/JS to call your API so you can demo full-stack.

Months 4–6 (if intensive) / Months 4–9 (if part-time)

• System design basics + microservices experiments.
• Build bigger project: e-commerce or scheduling app with:
  • auth service, product service, order service (or simpler: blog + comments + search)
  • background jobs (order processing), message queue
  • monitoring/logging basics
• Start interview prep: weekly algorithm practice, a few mock interviews.

Months 6–12 (final polish for both tracks)

• Contribute to an open-source project or build a public portfolio project with strong README and architecture docs.
• Network: GitHub, LinkedIn, meetups, referrals.
• Apply to jobs, do mock interviews, iterate on resume and interview answers.

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4) Concrete projects (in order of increasing difficulty)

Build these and put each in GitHub with: README, architecture diagram, tests, Dockerfile, CI, and a deployed link.

1. Notes API (CRUD) — Postgres, Express/Flask, JWT auth, unit tests, Docker, deployed.
2. Authentication system — Email/password, password reset, sessions/JWT, refresh tokens.
3. Blog platform — Users, posts, comments, image upload, pagination, search.
4. Task queue demo — Submit jobs (e.g., image conversion), process with worker (Bull/Celery), show queue UI.
5. E-commerce prototype — Product catalog, orders, payments mock, order processing pipeline.
6. Real-time chat — WebSocket or Socket.IO, rooms, presence, deploy.
7. Microservice split — API gateway + two small services + message broker to show interservice comms.

For each project include:

• Architecture diagram (draw.io screenshot or Markdown diagram).
• How to run locally (Docker compose).
• How to deploy and credentials (no secrets).
• Tests and badges (CI passing).

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5) Interview preparation (how to practice)

• Algorithm practice: do problems on LeetCode/HackerRank. Start easy → medium. Schedule:
  • Intensive: 1–2 problems daily (30–60 min).
  • Part-time: 3–4 problems/week.
• System design: study basic patterns; practice 1 design per week (URL shortener, tiny social feed).
• Mock interviews: use Pramp, Interviewing.io, or pair with peers. Do 1 mock/week in the last 8 weeks.
• Behavioral: prepare STAR stories for 8–10 experiences (teamwork, conflict, project ownership).

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6) Tools + nitty gritty you’ll use daily

• Editor: VS Code (extensions: Prettier, ESLint, GitLens).
• DB tools: psql CLI, PgAdmin, DBeaver.
• API testing: Postman or Insomnia.
• Version control: Git + GitHub (PR workflow).
• Containers: Docker, docker-compose.
• CI/CD: GitHub Actions.
• Cloud: learn basics of one cloud (AWS, GCP, or Azure). Start with deploying apps to a simple platform (Render / Railway / Heroku) then learn EC2/ECS or App Engine.
• Monitoring: simple logging to console, then explore Prometheus/Grafana later.

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7) Weekly study schedule templates

Intensive (40 hours/week) — sample week

• Mon–Fri: 6–7 hours/day
  • 2–3 hours course/tutorial
  • 2 hours hands-on coding (project)
  • 1 hour reading/docs + 30min algorithms
• Sat: 6 hours — deep work: architecture, tests, CI.
• Sun: rest + 1–2 hours review.

Part-time (20 hours/week) — sample week

• Mon/Wed/Fri: 2.5 hours each — tutorials + exercises.
• Tue/Thu: 2.5 hours each — hands-on project work.
• Sat: 4 hours — deep work, tests, deployment.
• Sun: 1 hour — algorithms or reading.

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8) What “intermediate developer” looks like (checkpoint)

You should be able to confidently say “I can …”:

• Build, test, and deploy a production-grade REST API.
• Design a small system and reason about tradeoffs.
• Use SQL and optimize queries; model relational data.
• Implement authentication and basic security practices.
• Write unit and integration tests; set up CI pipelines.
• Containerize apps with Docker and deploy to cloud or PaaS.
• Use Redis for caching and a queue for background jobs.
• Debug and profile backend issues; interpret logs.
• Communicate about architecture, write good READMEs and docs.
  If you can do these, you’re intermediate.

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9) Resources (pick ones that fit your learning style)

Free: freeCodeCamp, MDN Web Docs, The Odin Project, SQLBolt, nodejs.org docs, Express docs, Django docs.
Structured / paid: Udemy (look for high-rated Node/TypeScript or Django courses), Frontend Masters (for deep backend topics), Educative.io (system design).
Books (for later): Designing Data-Intensive Applications (useful for architecture), Clean Code (coding craftsmanship).

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10) First 30 days — exact action plan (no fluff)

Follow this if you want immediate focus.

Days 1–7:

• Setup tools, GitHub, Node or Python.
• Finish 10 small exercises (loops, functions, arrays).
• Push first repo.

Days 8–15:

• Complete a beginner tutorial for Express or Flask.
• Learn SQL basics and create a Postgres DB locally.

Days 16–23:

• Start the Notes API: routing, DB connection.
• Commit daily, open PRs to yourself — practice writing good commit messages.

Days 24–30:

• Add JWT auth and tests for basic endpoints.
• Dockerize and push to GitHub.
• Deploy to free tier.

At day 30: you’ll have a deployed project, GitHub repo, and the confidence to continue to bigger features.

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11) How to get your first job / internships

• Polish 2–3 showcase projects with documentation.
• Add a short technical writeup on each (1–2 pages).
• Contribute to small open-source issues (label “good first issue”).
• Apply to many roles, tailor your resume, include links to GitHub and deployed apps.
• Network: LinkedIn posts about your projects, join local dev meetups, ask for informational interviews.
• Prepare 10–20 STAR stories for behavioral interviews.

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12) Common pitfalls + how to avoid them

• Pitfall: jumping between too many technologies.
  Fix: pick one stack and finish projects with it.
• Pitfall: projects without tests or docs.
  Fix: always add at least basic tests and README.
• Pitfall: focusing only on tutorials and not building.
  Fix: build small projects from day 10 onward.
• Pitfall: ignoring algorithms.
  Fix: 20–45 minutes, 3× weekly practice.

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13) Final checklist — are you ready to apply?

You’re ready when:

• You have 2–3 public projects (deployed + repo + README).
• You can explain architectural decisions for those projects.
• You can solve common interview coding problems (medium level).
• You understand deployment and can debug production logs.
• Your resume and LinkedIn highlight your projects and tech stack.

Month 1: Foundations + First Fine-Tune

Goal: Learn Hugging Face + PyTorch basics and fine-tune your first model.

Skills

Python (NumPy, Pandas, basic classes).

PyTorch basics (tensors, training loops).

Transformers (attention, embeddings, tokenization).

Hugging Face: transformers, datasets, peft.

Projects

Fine-tune DistilBERT on sentiment classification.

Fine-tune a small LLaMA/Mistral model for Q&A.

Milestone:

✅ You can load a model from Hugging Face, fine-tune it, evaluate it, and push it back to the Hugging Face Hub.

Month 2: Fine-Tuning Mastery

Goal: Practice multiple fine-tuning strategies + domain applications.

Skills

LoRA / QLoRA (parameter-efficient fine-tuning).

Adapters, prompt-tuning.

Vector databases (FAISS) + Retrieval-Augmented Generation (RAG).

Projects

Fine-tune LLaMA or Mistral with LoRA for domain-specific chatbot (e.g., customer support, medical, or legal).

Build a RAG pipeline (fine-tuned model + vector DB).

Fine-tune Stable Diffusion with DreamBooth for custom branding.

Milestone:
✅ You can adapt models to specific industries and optimize GPU cost with LoRA/QLoRA.

Month 3: Deployment + Portfolio

Goal: Learn to deploy fine-tuned models + build job-ready portfolio.

Skills

Model serving (Hugging Face Inference API, AWS Sagemaker, Docker).

Quantization for cheaper inference.

Experiment tracking (Weights & Biases).

Projects

Deploy your fine-tuned chatbot as an API or web app.

Optimize with quantization (run on CPU or small GPU).

Create a portfolio repo with 3–4 end-to-end fine-tuning demos.

Milestone:
✅ You have public projects + live demos proving you can fine-tune, optimize, and deploy models.

📊 Condensed Timeline

Month 1: Learn → fine-tune first models (DistilBERT + LLaMA).

Month 2: Master fine-tuning techniques (LoRA, QLoRA, RAG, multimodal).

Month 3: Deploy + portfolio (live API, Hugging Face Hub, blog posts).

A church attendance plugin for children department. Keep track of children clock in and clock out. Use the admin dashboard to manage passcode to ensure only authorized attendance are recorded