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UNIVERSITAS APERTA · SCIENTIA OMNIBUS PATET · MMXXVI ✦ ✦ Open University Universitas Aperta · Scientia Omnibus Patet

Programmes · 10 courses · ≈ 44 ECTS

Foundations of Machine Learning

From first derivative to first trained network: the mathematics, the statistics, and the core methods, in the order that makes each step feel inevitable rather than mysterious.

  1. Mathematical foundations

    MATH 110 is four hours of geometric intuition — watch it immediately before MATH 201.

    19 ECTS
    MATH 101 Single Variable Calculus MIT OpenCourseWare · David Jerison 6 ECTS MATH 110 Essence of Linear Algebra 3Blue1Brown · Grant Sanderson 1 ECTS MATH 201 Linear Algebra MIT OpenCourseWare · Gilbert Strang 6 ECTS STAT 101 Introduction to Probability Harvard University · Joseph K. Blitzstein 6 ECTS

  2. Programming

    Already a confident programmer? Skip ahead — CS 110 exists to make the labs in later stages routine.

    4 ECTS
    CS 110 Introduction to CS and Programming in Python MIT OpenCourseWare · Ana Bell, Eric Grimson, John Guttag 4 ECTS

  3. Core machine learning

    8 ECTS
    ML 201 Machine Learning Specialization DeepLearning.AI & Stanford Online · Andrew Ng 4 ECTS STAT 210 Statistical Learning Stanford Online · Trevor Hastie, Robert Tibshirani 4 ECTS

  4. Deep learning

    ML 210 and ML 220 approach the same summit from opposite faces — top-down practice and bottom-up construction. Ambitious students take both.

    13 ECTS
    ML 210 Practical Deep Learning for Coders fast.ai · Jeremy Howard 4 ECTS ML 220 Neural Networks: Zero to Hero Andrej Karpathy 3 ECTS ML 301 Machine Learning (CS229) Stanford University · Andrew Ng 6 ECTS
On completion

On completing this programme you can read the machine learning literature without flinching: you have done calculus and linear algebra properly, reasoned about probability, trained classical models by hand, and built neural networks from scratch.