Learn Python: A Course Designed Specifically for Data Science and AI

From "What's Python?" to analyzing real datasets in just 3 hours

🚀 Start Learning Now - No Setup Required!

Click any notebook below to open it directly in Google Colab:

Module 1: Python Fundamentals

• Notebook 1: Python Basics (20 min)
• Notebook 2: Control Structures (25 min)

Module 2: Data Structures

• Notebook 3: Lists and Data Structures (25 min)
• Notebook 4: Dictionaries (25 min)

Module 3: Data Science Libraries

• Notebook 5: Pandas Preview (15 min)
• Notebook 6: Functions and Modules (20 min)
• Notebook 7: NumPy Fundamentals (25 min)
• Notebook 8: Matplotlib Basics (25 min)

Module 4: Machine Learning

• Notebook 9: Scikit-Learn Basics (45 min)

Capstone Project

• Notebook 10: Weather Data Analysis (45-60 min)

💡 Pro Tip: Google Colab provides a free Python environment with many data science libraries pre-installed!

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Course Overview

This comprehensive course bridges the gap between complete programming beginners and functional data science practitioners. Unlike typical Python courses that teach theoretical concepts, every lesson directly prepares you for real data science work.

Duration: 4+ hours | Prerequisites: None | Goal: Master Python fundamentals and build your first ML models

What Makes This Course Different?

🎯 Data Science Focused - Every concept connects to real workflows: list slicing (X[0:3]) for ML, NumPy operations, and string formatting for analysis reports.

📊 Real-World Context - Calculate financial interest, analyze weather data, and work with realistic datasets instead of theoretical examples.

🏗️ Progressive Building - Each notebook builds on the previous one with concepts introduced when needed.

Learning Objectives

Master these essential data science skills:

• Core Python: Variables, data structures, control flow, functions
• Data Science Libraries: NumPy arrays, Matplotlib visualization, Pandas basics
• Machine Learning: Build classification and regression models with scikit-learn
• Real Application: Read ML notebooks, debug code, solve data problems

Getting Started

Prerequisites: None! Perfect for business professionals, researchers, students, or anyone curious about data science.

Time Investment: 3 hours core learning + 2-3 hours practice

🛠️ Local Setup (Optional)

For local development, clone the repository and run:

# Quick setup script
./setup.sh

# Or manually:
python3 -m venv venv
source venv/bin/activate  # Windows: venv\Scripts\activate
pip install -r requirements.txt
jupyter notebook

Start with 01_python_basics.ipynb and work through in order.

Course Files

📁 Data-Science-AI-Python-Course/
├── 📓 01_python_basics.ipynb          # Variables, data types, financial calculations
├── 📓 02_control_structures.ipynb     # Conditionals, loops, temperature analysis  
├── 📓 03_lists_data_structures.ipynb  # Lists, indexing, data manipulation
├── 📓 04_dictionaries_advanced.ipynb  # Dictionaries, nested structures, APIs
├── 📓 05_pandas_preview.ipynb         # First taste of data science ecosystem
├── 📓 06_functions_modules.ipynb      # Clean, reusable code practices
├── 📓 07_numpy_fundamentals.ipynb     # Numerical computing, ML foundations
├── 📓 08_matplotlib_basics.ipynb     # Professional data visualization
├── 📓 09_capstone_project.ipynb      # Comprehensive weather analysis
├── � 10_scikit_learn_basics.ipynb   # Machine learning with scikit-learn
├── �📄 requirements.txt               # Python package dependencies
└── 🛠️ setup.sh                       # Automated environment setup

What's Next?

After completing this course, you'll be ready to:

• Build advanced ML models and tune hyperparameters
• Work with deep learning frameworks (TensorFlow, PyTorch)
• Handle real-world data challenges and preprocessing
• Deploy models to production environments

Quick Troubleshooting

Common fixes:

# Jupyter won't start
pip install --upgrade jupyter

# Import errors  
pip install -r requirements.txt

# Virtual environment issues
rm -rf venv && python3 -m venv venv && source venv/bin/activate

Resources & Support

• 📘 Official Python Tutorial
• 🔢 NumPy Documentation
• 📊 Matplotlib Tutorials
• 🐼 Pandas Getting Started
• 🏆 Kaggle Learn - Free data science courses

📚 Related Reading: Learn Python for Data Science

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🤝 Contributing

We welcome contributions! See CONTRIBUTING.md for guidelines.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Remember: Every expert was once a beginner. The only difference is they started.

What will you build with your data science skills? 🚀

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Made with ❤️ for the Data Science Community

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