🚀 Roadmap to Master Data Science in 60 Days! 📊🧠

📅 Week 1–2: Foundations
🔹 Day 1–5: Python basics (variables, loops, functions)
🔹 Day 6–10: NumPy Pandas for data handling

📅 Week 3–4: Data Visualization Statistics
🔹 Day 11–15: Matplotlib, Seaborn, Plotly
🔹 Day 16–20: Descriptive stats, probability, distributions

📅 Week 5–6: Data Cleaning EDA
🔹 Day 21–25: Missing data, outliers, data types
🔹 Day 26–30: Exploratory Data Analysis (EDA) projects

📅 Week 7–8: Machine Learning
🔹 Day 31–35: Regression, Classification (Scikit-learn)
🔹 Day 36–40: Model tuning, metrics, cross-validation

📅 Week 9–10: Advanced Concepts
🔹 Day 41–45: Clustering, PCA, Time Series basics
🔹 Day 46–50: NLP or Deep Learning (basics with TensorFlow/Keras)

📅 Week 11–12: Projects Deployment
🔹 Day 51–55: Build 2 projects (e.g., Loan Prediction, Sentiment Analysis)
🔹 Day 56–60: Deploy using Streamlit, Flask + GitHub

🧰 Tools to Learn:
• Jupyter, Google Colab
• Git GitHub
• Excel, SQL basics
• Power BI/Tableau (optional)

💬 Tap ❤️ for more!