This course teaches the basics of the most important mathematics for data science applications. You will learn:
- what vectors and matrices are, and how they can be added and multiplied
- how to compute the determinant, inverse, eigenvalues, and eigenvectors of a matrix (and what all of these things are)
- how Principal Component Analysis works
- the basics of set theory and propositional logic
- how to compute and interpret probabilities
- what probability distributions and Markov Chains are, and what they are used for
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- Vectors and matrices
- Matrix (de)composition
- Basic set theory
- Propositional logic
- Probability
- Probability distributions
- Markov Chains
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We start with a refresher of high-school level mathematics. This course is specifically intended for students who do not have any other mathematics courses in their bachelor programme
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A vague memory of high-school mathematics should be sufficient
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This course is only for students of the interfacultary minor Data Science, who do not have any other mathematics courses in their bachelor programme
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