Foundations

Mathematical Foundations

Linear algebra, calculus, probability, statistics and optimisation — the maths behind ML

2,093
lessons
Skills in this topic
View full skill map →
Maths for ML
beginner
Multiply matrices and compute dot products
Probability & Statistics
beginner
Calculate conditional probability and Bayes' theorem
Optimisation
intermediate
Implement gradient descent from scratch
Information Theory
intermediate
Calculate Shannon entropy and cross-entropy loss
📚 Continue on Coursera External links · Free to audit
1 / 3 View all →
Introduction to Python for Scientific Computing
📚 External: Coursera ↗
Self-paced
Introduction to Python for Scientific Computing
Opens on Coursera ↗
Measures of Central Tendency
📚 External: Coursera ↗
Self-paced
Measures of Central Tendency
Opens on Coursera ↗
Operating Systems
📚 External: Coursera ↗
Self-paced
Operating Systems
Opens on Coursera ↗
Kaizen Event: Become a Certified Kaizen Event Specialist
📚 External: Coursera ↗
Self-paced
Kaizen Event: Become a Certified Kaizen Event Specialist
Opens on Coursera ↗
Statistical Estimation for Data Science and AI
📚 External: Coursera ↗
Self-paced
Statistical Estimation for Data Science and AI
Opens on Coursera ↗
Foundations of Purchasing: Principles and Practices
📚 External: Coursera ↗
Self-paced
Foundations of Purchasing: Principles and Practices
Opens on Coursera ↗