Probability, statistics, optimization, and the rigorous foundations of modern AI.
45
Courses
6
Subcategories
1431h+
Total Hours
All levels
Difficulty Range
Step 0 Foundations 0.1 Calculus & Tools for Statistics & ML
Master the essential concepts of calculus and discover how they are applied in statistics and machine learning. This course covers derivatives, integrals, and practical tools for data analysis, with hands-on exercises and real-world examples.
Step 0 Foundations 0.2 Epistemology & Theory of Knowledge
Explore the foundations of knowledge and scientific reasoning. Learn about epistemology, the philosophy of science, and how we build, justify, and question knowledge in the context of data and research.
Step 1 Program Introduction
Get an overview of the program structure, learning objectives, and key resources. This introduction will guide you through the curriculum and help you make the most of your learning journey.
Step 1 Systems Theory 1.1 Dynamical Systems
Learn the principles of dynamical systems, including stability, chaos, and feedback loops. This course provides mathematical foundations and real-world applications in engineering, biology, and economics.
Step 1 Systems Theory 1.2 Complex Adaptive Systems
A generic course about Complex Adaptive Systems. Content coming soon.
Step 2 Stochastic Dynamics Probability 2.1 Measure Theory
A generic course about Measure Theory. Content coming soon.
Step 2 Stochastic Dynamics Probability 2.2 Probability Theory
A generic course about Probability Theory. Content coming soon.
Step 2 Stochastic Dynamics Probability 2.3 Usual Probability Distributions
A generic course about Usual Probability Distributions. Content coming soon.
Step 2 Stochastic Dynamics Probability 2.4 Asymptotic Statistics
A generic course about Asymptotic Statistics. Content coming soon.
Step 2 Stochastic Dynamics Probability 2.6 Information Geometry
A generic course about Information Geometry. Content coming soon.
Step 7 Non Linear Models Examples 7.2 Percolation Theory
A generic course about Percolation Theory. Content coming soon.
Step 7 Non Linear Models Examples 7.3 Spatial Statistics
A generic course about Spatial Statistics. Content coming soon.