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  1. Home
  2. Learning Paths

Mathematics for Machine Learning Learning Path

Mathematics for Machine Learning is a Specialization designed by Coursera. It consists of three courses and can be completed in four months .

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Description

For a lot of higher level courses in Machine Learning and Data Science, you find you need to freshen up on the basics in mathematics - stuff you may have studied before in school or university, but which was taught in another context, or not very intuitively, such that you struggle to relate it to how it’s used in Computer Science. This specialization aims to bridge that gap, getting you up to speed in the underlying mathematics, building an intuitive understanding, and relating it to Machine Learning and Data Science.

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Free Learning Paths by Career Track

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Included Courses

Coursera
Imperial College London
Free
1. Mathematics for Machine Learning: Linear Algebra

19 hours

Beginner

264,495
Jupyter Python Algorithms Applied Mathematics Data Science Data Sets Functions
Coursera
Imperial College London
Free
2. Mathematics for Machine Learning: Multivariate Calculus

18 hours

Beginner

99,258
Python Applied Mathematics Data Analysis Functions Machine Learning Neural Networks
Coursera
Imperial College London
Free
3. Mathematics for Machine Learning: PCA
Marc Peter Deisenroth

18 hours

Intermediate

63,932
Jupyter NumPy Python Algorithms Applied Mathematics Data Analysis Data Sets Dimension Reduction
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