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Free module

Calculus and optimisation for computing

Learn calculus and optimisation hands on: slopes, derivatives, gradients, gradient descent and least squares line fitting, worked in Python notebooks.

6 lessons380 min lessonFoundations

The lessons

Each lesson is free to read in full. Create a free account to run its commands in a live lab and to sit its quizzes and tasks.

  1. 1 · Container lab

    Rate of change and slope

    I can estimate how fast something changes from numbers.

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  2. 2 · Container lab

    Derivative rules for polynomials

    I can use the rules for the derivative of a simple function.

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  3. 3 · Container lab

    Partial derivatives and the gradient

    I can find the gradient of a function of two variables.

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  4. 4 · Container lab

    How gradient descent works

    I can minimise a function by stepping downhill.

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  5. 5 · Container lab

    Least squares line fitting

    I can fit a line to points by minimising the squared error.

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  6. 6 · Container lab

    Local minima and SciPy optimisers

    I can use SciPy's optimiser and say when descent gets stuck.

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Worked in a real lab

Every lesson of this module is worked in a lab started for you alone. The labs it uses:

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