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Understand Mathematics, Understand Computing : Discrete Mathematics That All Computing Students Should Know

Principles of Parallel Scientific Computing : A First Guide to Numerical Concepts and Programming Methods

A Beginner’s Guide to Statistics for Criminology and Criminal Justice Using R

Sets, Logic and Maths for Computing

Explorations in Number Theory : Commuting through the Numberverse

Modeling Reality with Mathematics

Statistics for Health Data Science : An Organic Approach

Computability

Probability in Electrical Engineering and Computer Science : An Application-Driven Course

Discrete Dynamics : Basic Theory and Examples

The Origins of Inequality : Mechanisms, Models, Policy

Numerical Python in Astronomy and Astrophysics : A Practical Guide to Astrophysical Problem Solving

MATLAB and Simulink Crash Course for Engineers

Applied Statistical Considerations for Clinical Researchers

Introduction to Algebraic Geometry

An Optimization Primer

Harmonic Analysis on the Real Line : A Path in the Theory

Quantitative Epidemiology

Orienteering Problems : Models and Algorithms for Vehicle Routing Problems with Profits

Public Systems Modeling : Methods for Identifying and Evaluating Alternative Plans and Policies

Computer Vision : Statistical Models for Marr's Paradigm

Applying Quantitative Bias Analysis to Epidemiologic Data

Geometric Multiplication of Vectors : An Introduction to Geometric Algebra in Physics

Explorations in Complex Functions

Statistical Field Theory for Neural Networks

An Introduction to Statistics with Python : With Applications in the Life Sciences

Luminescence : Data Analysis and Modeling Using R

Statistical Foundations, Reasoning and Inference : For Science and Data Science

Solomon Golomb’s Course on Undergraduate Combinatorics

Multivariate Data Analysis on Matrix Manifolds : (with Manopt)

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