📊 DATA SCIENCE JOURNEY — Prince Singh

This repository is a structured log of my Data Science journey, where I learn, implement, and track progress across concepts — from SQL & Python fundamentals to Machine Learning and API deployment.

Unlike typical repos, this is not just notes — it is a consistency-driven, implementation-first learning system.

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🚀 About Me

Hi, I'm Prince Singh 👋
🎓 B.Tech CSE (Data Science Specialization)
💡 Focused on Data Science, Machine Learning & real-world systems

• Strong in: C, C++, Python, SQL
• Skilled in: Data Analysis (Pandas, NumPy), Power BI, Excel
• Currently working on: ML systems & FastAPI-based deployments
• Building: Fraud Detection Systems, AI-based solutions

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📂 Repository Structure (Learning + Implementation Flow)

This repo follows a real learning progression (visible via commits) 👇

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🟡 SQL & Data Fundamentals

• 30 Days Micro SQL → SQL practice streak
• 50 SQL Questions → Core SQL problem solving
• SQL → Queries & real practice
• Database → Structured data understanding

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🔵 Python Core & Data Handling

• Functions → Python fundamentals
• File Handling → Working with files
• NumPy → Arrays, operations, broadcasting, slicing
• Pandas → DataFrames, cleaning, transformation

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🟢 Data Analysis & Visualization

• Matplotlib → Visualization basics
• Seaborn → Statistical visualization
• Plotly → Interactive visualization

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🧹 Data Processing

• Data Cleaning → Real-world dataset preprocessing

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📊 Statistics

• Statistics → Core mathematical foundation for ML

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🤖 Machine Learning

• Machine Learning → Algorithms implementation
• Machine Learning Advanced → Extended ML concepts
• Feature Engineering → Data preprocessing techniques

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⚡ Backend + Deployment

• FastAPI → Model deployment & APIs
• Pydantic → Data validation for APIs

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📈 What Makes This Repo Different

✔️ Consistency-based learning (visible commit history)
✔️ Hands-on implementations, not just theory
✔️ Progress tracked from basics → advanced
✔️ Real transition: SQL → ML → Deployment
✔️ Practical focus on building usable systems

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🔥 Recent Highlights (from commits)

• ✅ Implemented ML algorithms (latest update)
• ✅ Built prediction model + input/output schemas (FastAPI)
• ✅ Completed Scikit-learn learning phases
• ✅ Practiced SQL (Window Functions, CTEs, Queries)
• ✅ Completed NumPy, Pandas, Matplotlib, Seaborn modules

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🛠️ Tech Stack

• Languages: Python, C++, SQL
• Libraries: NumPy, Pandas, Matplotlib, Seaborn, Scikit-learn
• Backend: FastAPI, Pydantic
• Tools: Jupyter Notebook, Power BI, Excel

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📊 Learning Philosophy

"Learn → Implement → Track → Improve"

This repository follows a strict cycle:

1. Learn concept
2. Implement practically
3. Commit progress
4. Build consistency

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🎯 Current Focus

• Advanced Machine Learning
• Model Deployment using FastAPI
• Real-world Data Science projects
• System design for ML applications

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📬 Connect With Me

• 📧 Email: prince.devds@gmail.com
• 💼 LinkedIn: https://www.linkedin.com/in/vibieprince
• 📸 portfolio: https://vibieprince.vercel.app

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⭐ Support

If you find this repository helpful, consider giving it a ⭐
It motivates me to keep building and sharing.

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🧭 Tagline

"Consistency + Implementation = Real Skills 🚀"