SQL Python Practice Pricing

Python fundamentals pandas NumPy

NumPy course

The NumPy essentials for data work and interviews: arrays, fast maths, random numbers and simple simulations, step by step.

0.1Why NumPy
0.2Creating arrays

1.1Shape and reshape
1.2Indexing and slicing
1.3Boolean masks

2.1Vectorised maths
2.2Aggregations and axis
2.3Broadcasting
2.4Missing values (NaN)

3.1Sorting and top k
3.2Unique values and counts
3.3Combining arrays
3.4Running totals and differences

4.1Random numbers
4.2Simulations

5.1Dot products and matrices
5.2Distances and similarity
5.3From scratch

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Company names only describe the kind of business in each exercise. All practice data is simulated, and the interviews and problems are our own, not real interview questions. We aren't affiliated with or endorsed by any company named.