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Tech Stack Roadmaps by Career Path ๐Ÿ›ฃ๏ธ

What to learn depending on the job youโ€™re aiming for ๐Ÿ‘‡

1. Frontend Developer
โฏ HTML, CSS, JavaScript
โฏ Git & GitHub
โฏ React / Vue / Angular
โฏ Responsive Design
โฏ Tailwind / Bootstrap
โฏ REST APIs
โฏ TypeScript (Bonus)
โฏ Testing (Jest, Cypress)
โฏ Deployment (Netlify, Vercel)

2. Backend Developer
โฏ Any language (Node.js, Python, Java, Go)
โฏ Git & GitHub
โฏ REST APIs & JSON
โฏ Databases (SQL & NoSQL)
โฏ Authentication & Security
โฏ Docker & CI/CD Basics
โฏ Unit Testing
โฏ Frameworks (Express, Django, Spring Boot)
โฏ Deployment (Render, Railway, AWS)

3. Full-Stack Developer
โฏ Everything from Frontend + Backend
โฏ MVC Architecture
โฏ API Integration
โฏ State Management (Redux, Context API)
โฏ Deployment Pipelines
โฏ Git Workflows (PRs, Branching)

4. Data Analyst
โฏ Excel, SQL
โฏ Python (Pandas, NumPy)
โฏ Data Visualization (Matplotlib, Seaborn)
โฏ Power BI / Tableau
โฏ Statistics & EDA
โฏ Jupyter Notebooks
โฏ Business Acumen

5. DevOps Engineer
โฏ Linux & Shell Scripting
โฏ Git & GitHub
โฏ Docker & Kubernetes
โฏ CI/CD Tools (Jenkins, GitHub Actions)
โฏ Cloud (AWS, GCP, Azure)
โฏ Monitoring (Prometheus, Grafana)
โฏ IaC (Terraform, Ansible)

6. Machine Learning Engineer
โฏ Python + Math (Linear Algebra, Stats)
โฏ Scikit-learn, Pandas, NumPy
โฏ Deep Learning (TensorFlow/PyTorch)
โฏ ML Lifecycle (Train, Tune, Deploy)
โฏ Model Evaluation
โฏ MLOps (MLflow, Docker, FastAPI)

React with โค๏ธ if you found this helpful โ€” content like this is rare to find on the internet!

Credits: https://whatsapp.com/channel/0029VahiFZQ4o7qN54LTzB17

Coding Projects: https://whatsapp.com/channel/0029VazkxJ62UPB7OQhBE502

ENJOY LEARNING ๐Ÿ‘๐Ÿ‘
  • โค 9
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