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Mathematics for AI

Linear algebra, calculus, probability and statistics for machine learning.

Course Duration: 10 hours​

What You'll Learn​

  • Linear algebra for ML
  • Calculus and optimization
  • Probability theory
  • Statistics for data science
  • Mathematical intuition for algorithms

Prerequisites​

  • High school mathematics
  • Python basics

Course Modules​

  1. Vectors and Vector Operations
  2. Matrices and Matrix Operations
  3. Eigenvalues and Eigenvectors
  4. Derivatives and Gradients
  5. Chain Rule and Backpropagation
  6. Optimization Techniques
  7. Probability Distributions
  8. Bayes Theorem
  9. Descriptive Statistics
  10. Inferential Statistics
  11. Applying Math to ML Algorithms

Key Concepts​

  • Vector spaces and transformations
  • Gradient descent optimization
  • Maximum likelihood estimation
  • Bayesian inference