Math for Machine Learning

About Math for Machine Learning

Would you like to learn a mathematics subject that is crucial for many high-demand lucrative career fields such as:

Computer Science

Data Science

Artificial Intelligence

If you're looking to gain a solid foundation in Machine Learning to further your career goals, in a way that allows you to study on your own schedule at a fraction of the cost it would take at a traditional university, this

online

course

is for you. If you're a working professional needing a

refresher

on machine learning or a

complete beginner

who needs to learn Machine Learning for the first time, this online course is for you.

Why you should take this online course

: You need to refresh your knowledge of machine learning for your career to earn a higher salary. You need to learn machine learning because it is a required mathematical subject for your chosen career field such as data science or artificial intelligence. You intend to pursue a masters degree or PhD, and machine learning is a required or recommended subject.

Why you should choose this instructor

: I earned my PhD in Mathematics from the University of California, Riverside. I have created many successful online math courses that students around the world have found invaluable—courses in linear algebra, discrete math, and calculus. In this course, I cover the core concepts such as:

Linear Regression

Linear Discriminant Analysis

Logistic Regression

Artificial Neural Networks

Support Vector Machines

After taking this course, you will feel

CARE-FREE AND CONFIDENT

. I will break it all down into bite-sized no-brainer chunks

.

I explain each definition and go through each example

STEP BY STEP

so that you understand each topic clearly. I will also be

AVAILABLE TO ANSWER ANY QUESTIONS

you might have on the lecture material or any other questions you are struggling with.

Practice problems

are provided for you, and

detailed solutions

are also provided to check your understanding.

30 day full refund if not satisfied.

Grab a cup of coffee and start listening to the first lecture. I, and your peers, are here to help. We're waiting for your insights and questions!

Enroll now!