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 →
Supply Chain Network Optimization Using MILP on RStudio
📚 External: Coursera ↗
Self-paced
Supply Chain Network Optimization Using MILP on RStudio
Opens on Coursera ↗
Machine Learning with R: Build, Analyze & Predict
📚 External: Coursera ↗
Self-paced
Machine Learning with R: Build, Analyze & Predict
Opens on Coursera ↗
 Supervised Machine Learning: Classification
📚 External: Coursera ↗
Self-paced
Supervised Machine Learning: Classification
Opens on Coursera ↗
Adobe InDesign CC: Part 1
📚 External: Coursera ↗
Self-paced
Adobe InDesign CC: Part 1
Opens on Coursera ↗
Python and Statistics for Financial Analysis
📚 External: Coursera ↗
Self-paced
Python and Statistics for Financial Analysis
Opens on Coursera ↗
Financial Risk Management and Market Analysis
📚 External: Coursera ↗
Self-paced
Financial Risk Management and Market Analysis
Opens on Coursera ↗