Run this notebook: Open in Colab Open in Kaggle 
import numpy as np

print(f"NumPy version: {np.__version__}")
print(f"\nNumPy is installed correctly! ✅")

# Quick test
arr = np.array([1, 2, 3, 4, 5])
print(f"\nTest array: {arr}")
print(f"Array shape: {arr.shape}")
print(f"Array dtype: {arr.dtype}")
print(f"\nYou're ready to start learning NumPy! 🎉")

📊 Content Statistics

  • Total Notebooks: 46 unique notebooks

  • Total Exercises: 100+ exercises

  • Advanced Tutorials: 10+ real-world projects

  • Space Saved: 82% reduction from original (188 MB → 34 MB)

💡 Study Tips

  1. Don’t Skip Basics - Even if you know Python, NumPy is different

  2. Type, Don’t Copy - Build muscle memory by typing examples

  3. Practice Daily - 30 minutes daily beats 3 hours weekly

  4. Use Documentation - Learn to read np.function? in Jupyter

  5. Experiment - Modify examples to test understanding

  6. Benchmark - Use %timeit to understand performance

📖 Additional Resources

🗺️ Next Steps

Ready to begin? Open 01-basics/01-NumPy Arrays.ipynb and start your NumPy journey!

For a detailed overview, see README.md