Course Curriculum
10 interactive lessons with real-time autograding
1
Module 1
The ndarray
Creating arrays from lists, arange, zeros, ones, shape, and dtypes.
2
Module 2
Indexing & Slicing
1D, 2D, and 3D array slicing, striding, and views vs copies.
3
Module 3
Boolean & Fancy Indexing
Masking, conditions, where(), and integer array indexing.
4
Module 4
Operations & Ufuncs
Element-wise arithmetic, math universal functions, and vector speed.
5
Module 5
Broadcasting
Broadcasting rules, dimension expansion with newaxis, and compatibility.
6
Module 6
Aggregations & Axes
sum, mean, std, min, max, argmin, argmax across specified axes.
7
Module 7
Reshaping & Combining
reshape, flatten, vstack, hstack, concatenate, and splitting.
8
Module 8
Linear Algebra
Matrix multiplication with dot/@, transpose, inverse, and det.
9
Module 9
Random, Sorting & Statistics
random generation, distributions, sort, argsort, and percentiles.
10
Module 10
Performance & Capstone
Vectorization benchmarking and numerical scientific computing capstone.