---
title: Applied Mathematics
description: Mathematics at work: modeling, optimization, numerical methods, and financial and cryptographic math.
category: mathematics
url: /subcategory/mathematics/applied-mathematics
---

# Applied Mathematics

Mathematics at work: modeling, optimization, numerical methods, and financial and cryptographic math.

## Available Subjects

### Convex Optimization

Convex optimisation solves problems where local optima are global. You will learn convex sets and functions, duality, algorithms and how to model engineering and machine-learning problems as convex programs.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 1 books, 1 courses, 1 websites, 1 papers

[Learn Convex Optimization](/subject/convex-optimization)

### Cryptography Math

This topic covers the mathematical foundations of secure communication, including number theory, abstract algebra, and probability. Learners will understand how algorithms like RSA and elliptic curve cryptography secure data transmission and digital signatures.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 4 books

[Learn Cryptography Math](/subject/cryptography-math)

### Financial Mathematics

Financial mathematics applies mathematical modeling and quantitative methods to financial markets. Learners will understand how to price derivative securities, manage portfolio risk, and model asset price movements using stochastic calculus and interest rate theory.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 3 books, 1 courses, 1 websites, 1 papers

[Learn Financial Mathematics](/subject/financial-mathematics)

### Finite Element Analysis & CFD

FEA and CFD simulate stresses, heat and fluid flow numerically. You will learn the underlying methods, meshing, boundary conditions, validation and how to use tools such as ANSYS, Abaqus or OpenFOAM responsibly.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 2 books, 3 courses

[Learn Finite Element Analysis & CFD](/subject/finite-element-analysis)

### Information Theory

Information theory quantifies information, compression and communication. You will learn entropy, mutual information, channel capacity and coding, and why these ideas underpin statistics and machine learning.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 4 books, 2 courses, 1 websites, 1 papers

[Learn Information Theory](/subject/information-theory)

### Mathematical Modeling

Mathematical modeling is the process of translating real-world phenomena into mathematical equations to analyze and predict behaviors. Learners will understand how to formulate, solve, and validate models across physics, biology, and social sciences.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 2 books, 2 courses, 1 websites

[Learn Mathematical Modeling](/subject/mathematical-modeling)

### Mathematics for Machine Learning

Machine learning rests on linear algebra, calculus, probability and optimisation. You will learn exactly the mathematics needed to read ML papers and textbooks, with the resources that teach it in that order.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 2 books, 1 courses, 2 papers

[Learn Mathematics for Machine Learning](/subject/statistics-for-machine-learning)

### Numerical Methods

Numerical methods are algorithms used to obtain approximate numerical solutions to mathematical problems that lack analytical solutions. Learners will understand how to solve differential equations, find roots, and perform numerical integration using computers.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 4 books, 1 courses, 2 websites

[Learn Numerical Methods](/subject/numerical-methods)

### Optimization

Optimization is the study of finding the best solution to a problem given a set of constraints. Learners will understand how to formulate and solve linear, non-linear, and integer programming problems using various mathematical algorithms.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 7 books, 1 courses

[Learn Optimization](/subject/optimization)

### Quantitative Finance

Quantitative finance applies mathematics to pricing and risk. You will learn stochastic calculus, derivatives pricing, portfolio theory and the programming and interview preparation used in quant roles.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 3 books, 2 courses, 3 websites

[Learn Quantitative Finance](/subject/quantitative-finance)

### Stochastic Calculus

Stochastic calculus handles calculus for random processes. You will learn Brownian motion, Itô's lemma, stochastic differential equations and the applications to option pricing and filtering.

**Difficulty:** Beginner, Intermediate, Advanced

**Resources:** 3 books, 1 websites

[Learn Stochastic Calculus](/subject/stochastic-calculus)

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View this page online: https://dantes.io/subcategory/mathematics/applied-mathematics