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What the HL AI bridging course covers
Applications and Interpretation HL is the course for modelling, statistics and technology: every paper is sat with a GDC, and HL adds topics such as matrices and graph theory. The six-week course makes sure the core skills underneath are solid:
- Week 1, number and algebra: expanding and factorising, the laws of indices, linear equations and systems, and scientific notation.
- Week 2, more algebra: algebraic fractions, expanding, factorising and solving quadratics, and rearranging formulae.
- Week 3, geometry and trigonometry: coordinate geometry, Pythagoras in 2D and 3D, and right-angled and non-right-angled trigonometry.
- Week 4, functions and modelling: function notation, inverse functions, linear models and exponentials.
- Week 5, statistics: measures of central tendency and dispersion, grouped data and bivariate data.
- Week 6, sets and probability: sets and Venn diagrams, tree diagrams, and independent and mutually exclusive events.
Each sub-topic has worked examples and practice questions with solutions, and each week ends with a four-question check. Week 1 also has two optional questions where AI marks a photo of your written working.
The 15-question diagnostic previews the HL-only content you will meet in DP1: the determinant of a 2 × 2 matrix, when two matrices can be multiplied, the number of edges in a graph from its vertex degrees, the difference between an Eulerian circuit and a Hamiltonian cycle, a vector cross product and the expected value of a binomial variable.