bestcourses is supported by learners. When you buy through links on our website, we may earn an affiliate commission. Learn more

Mathematical Foundation For Machine Learning and AI

Learn the core mathematical concepts for machine learning and learn to implement them in R and python

4.55 / 5.0
7205 students4 hours 16 minutes

Created by Eduonix Learning Solutions, offered on Udemy

bestcourses score™

Student feedback

7.1/10

To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 7205 students which left 1216 reviews at an average rating of 4.55. Impressive!

Course length

9/10

We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 4 hours 16 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 7 hours 54 minutes.

Overall score

6.6/10

This course currently has a bestcourses score of 6.6/10, which makes it an average course. Overall, there are probably better courses available for this topic on our platform.

Description

Artificial Intelligence has gained importance in the last decade with a lot depending on the development and integration of AI in our daily lives. The progress that AI has already made is astounding with the self-driving cars, medical diagnosis and even betting humans at strategy games like Go and Chess.

The future for AI is extremely promising and it isn’t far from when we have our own robotic companions. This has pushed a lot of developers to start writing codes and start developing for AI and ML programs. However, learning to write algorithms for AI and ML isn’t easy and requires extensive programming and mathematical knowledge.

Mathematics plays an important role as it builds the foundation for programming for these two streams. And in this course, we’ve covered exactly that. We designed a complete course to help you master the mathematical foundation required for writing programs and algorithms for AI and ML.

The course has been designed in collaboration with industry experts to help you breakdown the difficult mathematical concepts known to man into easier to understand concepts. The course covers three main mathematical theories: Linear Algebra, Multivariate Calculus and Probability Theory.

Linear Algebra – Linear algebra notation is used in Machine Learning to describe the parameters and structure of different machine learning algorithms. This makes linear algebra a necessity to understand how neural networks are put together and how they are operating.

It covers topics such as:

  • Scalars, Vectors, Matrices, Tensors

  • Matrix Norms

  • Special Matrices and Vectors

  • Eigenvalues and Eigenvectors

Multivariate Calculus – This is used to supplement the learning part of machine learning. It is what is used to learn from examples, update the parameters of different models and improve the performance.

It covers topics such as:

  • Derivatives

  • Integrals

  • Gradients

  • Differential Operators

  • Convex Optimization

Probability Theory – The theories are used to make assumptions about the underlying data when we are designing these deep learning or AI algorithms. It is important for us to understand the key probability distributions, and we will cover it in depth in this course.

It covers topics such as:

  • Elements of Probability

  • Random Variables

  • Distributions

  • Variance and Expectation

  • Special Random Variables

The course also includes projects and quizzes after each section to help solidify your knowledge of the topic as well as learn exactly how to use the concepts in real life.

At the end of this course, you will not have not only the knowledge to build your own algorithms, but also the confidence to actually start putting your algorithms to use in your next projects.

Enroll now and become the next AI master with this fundamentals course!

What you will learn

  • Refresh the mathematical concepts for AI and Machine Learning
  • Learn to implement algorithms in python
  • Understand the how the concepts extend for real world ML problems

Requirements

  • Basic knolwedge of python is assumed as concepts are coded in python and R
Udemy logo
Available on

Udemy

With almost 200,000 courses and close to 50 million students, Udemy is one of the most visited online learning platforms. Popular topics include software development, the digital economy, but also more traditional topics like cooking and music.

Frequently asked questions

  • Price: $49.99
  • Platform: Udemy
  • Language: English
  • 4 hours 16 minutes
Mathematical Foundation For Machine Learning and AI thumbnail

bestcourses score: 6.6/10

There might be better courses available for this topic.