# General query: Multivariate calculus

Hi, I’m a beginner. For this course Calculus for Machine Learning & Data Science, does it cover “Multivariate Calculus” ? Thank you

Hello @Matt5129
Welcome to the discourse community. Thanks a lot for bringing this question up.

It appears that the only topic that is covered in the field of Multivariate calculus is “Multivariate Newton’s method”.

Here is a list of the topics of the “Calculus for Machine Learning & Data Science” :

Calculus for Machine Learning and Data Science:

#### Week 1: Functions of one variable: Derivative and optimization

Lesson 1: Derivatives

• Example to motivate derivatives: Speedometer
• Derivative of common functions (c, x, x^2, 1/x)
• Meaning of e and the derivative of e^x
• Derivative of log x
• Existence of derivatives
• Properties of derivative

Lesson 2: Optimization with derivatives

Video 1: Intro to optimization: Temperature example

Video 2: Optimizing cost functions in ML: Squared loss

Video 3: Optimizing cost functions in ML: Log loss

#### Week 2: Functions of two or more variables: Gradients and gradient descent

• Example to motivate gradients: Temperature
• Optimization using slope method: Linear regression

• Optimization using gradient descent: 1 variable
• Optimization using gradient descent: 2 variable
• Gradient descent for linear regression

#### Week 3: Optimization in Neural Networks and Newton’s method

Lesson 1: Optimization in Neural Networks

• Perceptron with no activation and squared loss (linear regression)
• Perceptron with sigmoid activation and log loss (classification)
• Two-layer neural network with sigmoid activation and log loss
• Mathematics of Backpropagation

Lesson 2: Beyond Gradient Descent: Newton’s Method

• Root finding with Newton’s method
• Adapting Newton’s method for optimization
• Second derivatives and Hessians
• Multivariate Newton’s method

A list of all courses under Mathematics for Machine Learning and Data Science Specialization