🌌 Oblivorax-Hub

Forge your path from code to cloud.
Learn programming, full-stack development, data science, AI, cloud, DevOps, and open-source contribution step by step.

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🚀 Why This Repository?

Technology is vast, and it’s easy to get lost. Oblivorax-Hub is a curated roadmap to help you master the tech stack layer by layer.
Whether you’re a beginner or aiming to become a full-stack + AI engineer with DevOps & cloud expertise, this repo will guide your journey.

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🧭 Table of Contents

• Phases
  • Phase 0: Core Foundations
  • Phase 1: Frontend Development
  • Phase 2: Backend Development
  • Phase 3: Data Analysis & Data Science Foundations
  • Phase 4: Machine Learning
  • Phase 5: Deep Learning & AI
  • Phase 6: Advanced AI + LLMs
  • Phase 7: Cloud & DevOps
  • Phase 8: Open Source & Scaling
• 🕐 Timeline
• 📂 How to Use This Roadmap
• 🤝 Contributing
• 📜 License

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🗺️ Phases

Phase 0: Core Foundations (2–3 months)

• Programming Language → Python / Java
• DSA → Arrays, Strings, Trees, Graphs
• CS Fundamentals → OS, Networking, DBMS
• Git & GitHub

🎯 Project: CLI tool (e.g., to-do list)

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Phase 1: Frontend Development (2–3 months)

• HTML, CSS, JavaScript
• React / Next.js
• Tailwind CSS

🎯 Project: Portfolio website + Weather App

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Phase 2: Backend Development (3–4 months)

• Node.js + Express / Spring Boot
• SQL + NoSQL (MongoDB)
• REST & GraphQL APIs
• Authentication & Deployment

🎯 Project: Blogging/E-commerce platform

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Phase 3: Data Analysis & Data Science Foundations (2–3 months)

• Python → Pandas, NumPy, Matplotlib
• SQL for Analytics
• Statistics & EDA

🎯 Project: Kaggle dataset analysis

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Phase 4: Machine Learning (3–4 months)

• Regression, Decision Trees, SVM, Clustering
• Scikit-learn, TensorFlow, PyTorch
• Model Evaluation

🎯 Project: Spam Classifier / Movie Recommender

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Phase 5: Deep Learning & AI (3–4 months)

• Neural Networks, CNNs, RNNs
• Transformers (attention mechanism)

🎯 Project: Face recognition / Sentiment analysis

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Phase 6: Advanced AI + LLMs (3–4 months)

• NLP → BERT, embeddings
• LLMs → GPT, LLaMA, fine-tuning
• Vector Databases (FAISS, Pinecone)
• MLOps basics

🎯 Project: Custom chatbot with fine-tuned LLM

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Phase 7: Cloud & DevOps (4–5 months)

• AWS / GCP / Azure
• CI/CD → GitHub Actions, Jenkins
• Docker & Kubernetes
• Terraform, Prometheus, Grafana

🎯 Project: Deploy ML app with Docker + CI/CD

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Phase 8: Open Source & Scaling (Ongoing)

• Open-source contributions
• Hackathons & Kaggle comps
• System Design

🎯 Project: Contribute to a real GitHub repo

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🕐 Rough Timeline

• Year 1: Foundations + Full-stack (Frontend + Backend)
• Year 2: Data Science + ML + AI
• Year 3: Cloud, DevOps, Advanced AI, Open Source

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📂 How to Use This Roadmap

1. Fork this repo and track your progress using the checkboxes ✅.
2. Complete the milestone projects at each stage.
3. Share your journey (blog posts, LinkedIn, GitHub commits).
4. Keep iterating — the tech world evolves fast!

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🤝 Contributing

Contributions are welcome! 🚀

• Found a missing topic? Open an issue.
• Have a project idea? Submit a pull request.
• Want to collaborate? Let’s build together.

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📜 License

This roadmap is licensed under the MIT License — you’re free to use, share, and modify it with attribution.

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⭐ If this roadmap helps you, star this repo to support the project!