Post🚀 Python Roadmap for Data Analytics 🐍📊🔥

🚀 Python Roadmap for Data Analytics 🐍📊🔥 🧠 STEP 1: Learn Python Basics ✔ Variables & Data Types ✔ Loops & Functions ✔ Lists, Tuples & Dictionaries ✔ File Handling ✔ Exception Handling 🛠 Tools to Learn: ✔ Jupyter Notebook ✔ Visual Studio Code 📊 STEP 2: Learn Data Handling ✔ Reading CSV & Excel Files ✔ Data Cleaning ✔ Handling Missing Values ✔ Data Transformation 🛠 Libraries to Learn: ✔ Pandas ✔ NumPy 📈 STEP 3: Learn Data Visualization ✔ Line Charts ✔ Bar Charts ✔ Pie Charts ✔ Heatmaps ✔ Interactive Dashboards 🛠 Visualization Libraries: ✔ Matplotlib ✔ Seaborn ✔ Plotly 🧠 STEP 4: Learn Statistics Basics ✔ Mean, Median & Mode ✔ Probability ✔ Correlation ✔ Hypothesis Testing ✔ A/B Testing ⚡ STEP 5: Learn SQL with Python ✔ Database Connections ✔ SQL Queries ✔ Fetching Data ✔ Data Integration 🛠 Libraries to Learn: ✔ sqlite3 ✔ SQLAlchemy ✔ PyMySQL 🤖 STEP 6: Learn Basic Machine Learning ✔ Regression ✔ Classification ✔ Clustering ✔ Model Evaluation 🛠 Frameworks to Learn: ✔ Scikit-learn ✔ XGBoost 📂 STEP 7: Learn Automation & Reporting ✔ Automating Reports ✔ Excel Automation ✔ API Data Collection ✔ Scheduling Tasks 🛠 Libraries to Learn: ✔ openpyxl ✔ requests ✔ schedule 🔥 STEP 8: Build Real Projects ✔ Sales Data Analysis ✔ HR Analytics Dashboard ✔ Customer Churn Analysis ✔ Financial Analytics ✔ Netflix Dataset Analysis Python Resources: https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L 💬 Tap ❤️ if this helped you!