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NUMPY FOUNDATIONS

Learn NumPy—the backbone of numerical computation in Python—to perform fast, vectorized operations on data.

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90 min total

8 Lessons

0 Completed

Module Content

NumPy vs Python Lists

Understand the difference between Python lists and NumPy arrays, and why NumPy is essential for data analysis.

15 minVideo

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NumPy Basics

Learn how to create, index, slice, and manipulate NumPy arrays for fast numerical operations.

15 minVideo

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QUIZ: Numpy Basics

25 minTutorial

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NumPy Broadcasting

Discover how broadcasting allows you to perform operations on arrays of different shapes efficiently.

15 minVideo

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NumPy Aggregations

Learn aggregation operations like sum, mean, min, max, and how to apply them along different axes.

15 minVideo

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NumPy Vectorization, Boolean Masks & Statistical Aggregations

Master the 2D axis mental model (axis=0 vs axis=1), NaN-safe statistical aggregations, boolean masking, cumulative sums, and percentiles.

12 minArticle

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QUIZ: Numpy Foundations

30 minTutorial

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ASSIGNMENT: NumPy Foundations

Create a Jupyter Notebook demonstrating core NumPy operations. Your submission should include: creating arrays from lists and using arange/linspace, reshaping and indexing arrays, element-wise operations and broadcasting, and statistical aggregations (mean, std, min, max, sum along axes). Use markdown cells to explain what each code cell does.