Learn NUMPY with Real Code Examples

Learn Python basics

Understand arrays, shapes, and dtypes

Master slicing, indexing, and broadcasting

Practice vectorized operations

Integrate with ML and data analysis libraries

Week 1: Array creation and basic operations

Week 2: Indexing, slicing, and masking

Week 3: Linear algebra and statistics

Week 4: Vectorization and performance optimization

Week 5: Integrate NumPy with Pandas, SciPy, or ML libraries

What is a NumPy ndarray?

Explain broadcasting in NumPy

How do you perform vectorized operations?

Difference between np.array, np.zeros, np.ones

How to save and load NumPy arrays?

array() = create ndarray

zeros()/ones() = initialize arrays

reshape() = change array shape

dot() = matrix multiplication

sum()/mean()/std() = statistics

Python for Data Analysis by Wes McKinney

NumPy Beginner’s Guide

Scientific Computing with Python 3

Mastering Numerical Computing with NumPy

Python Data Science Handbook

Official NumPy tutorials

Jupyter notebooks online

MOOCs like SciPy and Python for Data Science

Community blog guides

Example projects on GitHub

https://numpy.org/

https://numpy.org/doc/stable/

https://github.com/numpy/numpy

NumPy GitHub repository

NumPy mailing list

StackOverflow

Reddit /r/Python and /r/DataScience

Tutorials and blog posts online

NumPy GitHub repository

NumPy mailing list and forums

StackOverflow

Reddit /r/Python and /r/MachineLearning

Tutorials and blogs online