fbpx

Best Machine Learning Courses

Benzinga Money is a reader-supported publication. We may earn a commission when you click on links in this article. Learn more.

Are you intrigued by the idea of machine learning? Maybe you’ve applied core concepts in the workplace and want to take your artificial intelligence expertise to a higher level. An online machine learning course can equip you with the tools needed to understand the basics or accelerate your career. 

Quick Look: Best Machine Learning Courses

Take a quick look at Benzinga’s top picks: 

What Makes a Machine Learning Course Great?

Keep the following considerations in mind as you explore machine learning course options and choose the right one for you. 

Starts with the Basics

The best machine learning courses begin with the fundamentals. No matter your skill level, it’s important to introduce or establish foundational information before moving into more complex material. 

Self-Paced

There are so many machine learning components so you want a course that allows you to work at your own pace. This gives you an ample amount of time to understand all the information presented in the lessons. 

Includes Real-Life Scenarios

You won’t know for sure whether you grasp the material until you have the opportunity to apply it. Consider courses with real-life scenarios to help you understand how to implement your newfound skills. Case studies are also beneficial because they give you hands-on experience in a setting where you can afford to make mistakes and overcome hurdles without serious implications.

Our Top Picks

We researched several online machine learning courses to compile our list of top picks. You’ll find classes from the leading online learning platforms — Coursera, LinkedIn Learning and Udemy. 

The classes are split into 3 categories by skill level: beginner, intermediate and advanced. You will also find a description and the enrollment fee for each course to make the best decision for you. 

Machine Learning Course for Beginners

New to machine learning? Start with these introductory courses. 

1. Machine Learning by Stanford University 

  • Who it’s for: Beginners 
  • Price: Free 

Are you interested in machine learning but aren’t quite sure how it works? Consider this beginner-level course that introduces effective machine learning techniques. You will also learn how to implement these techniques in your everyday life and use them to resolve issues. 

Core topics covered in the course include linear regression, linear algebra, logistic regression, regularization, neutral networks and support vector machines. You’ll also learn more about dimensionality reduction, anomaly detection and recommender systems. 

A seat in this 10-module course is free. Expect to spend 56 hours working through the course material, which includes videos, reading and quizzes. 

The class is led by Andrew Ng, adjunct professor at Stanford University. He’s also the founder of Landing AI and the co-founder of Coursera.

Get this course. 

2. Machine Learning Foundations: A Case Study Approach by the University of Washington 

  • Who it’s for: Beginners 
  • Price: Free

Offered by the University of Washington, this free course is a component of the Machine Learning Specialization. It is designed for individuals who want to learn how machine learning can help analyze data and improve business operations. 

This course delivers invaluable knowledge through the following case studies:

  • Regression: Predicting House Prices
  • Classification: Analyzing Sentiment 
  • Clustering and Similarity: Retrieving Documents
  • Recommending Products 
  • Deep Learning: Searching for Images 

When you reach the finish line, you’ll have the skills to apply the techniques learned in each case study in the field. You will also be able to use Python to implement your new skillset. 

Instructor Carlos Guestrin is an Amazon professor of machine learning in the computer science and engineering department and Emily Fox is an Amazon professor of machine learning in statistics. 

Get this course. 

Applied Machine Learning: Foundations

3. Applied Machine Learning: Foundations by LinkedIn Learning (Formerly Lynda.com)

In a little over 2.5 hours, you can learn the fundamentals of machine learning in this beginner-level course from LinkedIn Learning. Led by Data Scientist Derk Jedamski, this class takes a closer look at various machine learning algorithms and ways to solve any problems that arise. 

The course begins with a primer on the basics of machine learning, followed by a lesson on exploratory data analysis and data cleaning. You will also learn the best practices for measuring success and optimizing a model. The final lesson covers the end-to-end pipeline process. 

Enrollment is included in the $29.99 monthly LinkedIn membership or you can grab a free seat by registering for a 1-month trial. Know how to write basic Python before you sign up. 

Get this course. 

Intermediate Machine Learning Courses 

These courses may be a good match if you understand the mechanics of machine learning and can apply critical concepts in the classroom or workplace.

4. Machine Learning: Regression by the University of Washington

  • Who it’s for: Intermediate students 
  • Price: Free

Machine Learning: Regression is the second part of the Machine Learning Specialization from the University of Washington. It explores the inner workings of regression models through a case study titled “Predicting Housing Prices.” 

The course is comprised of 5 modules:

  • Multiple Regression 
  • Assessing Performance
  • Ridge Regression
  • Feature Selection and Lasso
  • Nearest Neighbors and Kernel Regression 

Lessons are taught through video content. Each module also includes supplementary reading and quizzes to test your comprehension of the material. 

Enrollment is free and it takes 35 hours to complete the course. 

It’s a good idea to complete Machine Learning Foundations: A Case Study Approach before you enroll. 

Get this course. 

5. Machine Learning: Classification by the University of Washington 

  • Who it’s for: Intermediate students 
  • Price: Free

Machine Learning: Classification is part 3 of the Machine Learning Specialization from the University of Washington. The case studies in this course focus on analyzing sentiment and predicting the likelihood of loan default. 

There are 9 lessons in the course:

  • Linear Classifiers and Logistic Regression
  • Learning Linear Classifiers 
  • Overfitting and Regularization in Logistic Regression
  • Decision Trees 
  • Preventing Overfitting in Decision Trees
  • Handling Missing Data 
  • Boosting 
  • Precision Recall 
  • Scaling to Huge Datasets and Online Learning 

Similar to the other courses in the specialization, the material is delivered through videos and reading. Each module ends with quizzes to identify areas where you are strong and offers areas where you’ll need to focus. 

Be sure to complete Machine Learning: Regression before you sign up.

Get this course. 

6. Machine Learning: Clustering and Retrieval by the University of Washington

  • Who it’s for: Intermediate students 
  • Price: Free

The final component of the Machine Learning Specialization from the University of Washington teaches the mechanics of clustering and retrieval through a case study titled “Finding Similar Documents.” 

You will learn techniques to help you quickly find the information you’re seeking without sifting through a pile of similar documents. The class also teaches you how to identify hot topics in these documents rapidly. 

Machine Learning: Clustering and Retrieval includes the following hands-on tasks: 

  • Nearest Neighbor Search
  • Clustering with K-Means 
  • Mixture Models 
  • Mixture Membership Modeling via Latent Dirichlet Allocation
  • Hierarchical Clustering

Ready to grab a free seat in this course? It’s a good idea to first complete Machine Learning: Classification

Get this course. 

Advanced Machine Learning Courses

Experienced professionals who are well-versed in artificial intelligence and use machine learning in the workplace may find these courses useful. 

Artificial Intelligence and Machine Learning Fundamentals

Expert • 53 videos • 7.8 hours

7. Artificial Intelligence and Machine Learning Fundamentals by Udemy

  • Who it’s for: Advanced students 
  • Price: $199.99

Offered by Packt Publishing, this course shows you how to use artificial intelligence to perform predictive analysis and solve real-world problems. It’s designed for data scientists and software developers who want to boost their skill set to improve machine learning projects. 

The $199.99 enrollment fee includes 53 lectures condensed into 8 hours of on-demand video. You’ll also receive a Certificate of Completion when you reach the end of the course. 

Know the Python programming language and high school level math before you register. 

Facilitator Zsolt Nagy is an engineering manager with an MSc in inference on ontologies and has several years of experience using artificial intelligence. 

Get this course. 

Machine Learning and AI: Support Vector Machines in Python

Expert • 73 videos • 8.9 hours

8. Machine Learning and AI: Support Vector Machines in Python by Udemy

  • Who it’s for: Advanced students 
  • Price: $199.99

Machine Learning and AI: Support Vector Machines in Python is another highly-rated course from Udemy for advanced professionals who seek a better understanding of the SVM. It’s also ideal if you want to understand the theory behind SVM and use it to resolve practical problems. 

Offered by Lazy Programmer Inc., this highly-rated course from Udemy includes lifetime access to 72 lectures jam-packed into 9 hours of on-demand video. It’s also backed by a 30-day money-back guarantee if you’re unsatisfied for any reason. 

Enrollment is $199.99. Have a working knowledge of calculus, matrix arithmetic, geometry and basic probability before you register. It’s also a good idea to understand Python, Numpy coding and Logistic Regression. 

Get this course. 

Machine Learning and AI: Advanced Decision Trees

9. Machine Learning and AI: Advanced Decision Trees by LinkedIn Learning (Formerly Lynda.com)

Master the QUEST and CS5.0 algorithms, as they relate to machine learning, in this advanced course from LinkedIn Learning. The course also explores other topics related to decision trees, including bagging, boosting, data modeling and data analysis.

Taught by Keith McCormick, the course contains the following modules:

  • Understanding QUEST
  • Understanding C5.0
  • Advanced Topics 

Course material is delivered through video. You’ll also have access to 1 project file and 2 chapter quizzes to enhance your learning experience. 

Enrollment is included in the $29.99 monthly LinkedIn membership. But if you aren’t a member, you can test drive the course by registering for a 1-month trial. 

Get this course. 

Choose the Right Machine Learning Course for You

Machine learning courses are offered at all skill levels and price points. We’ve included a variety of options to help you master the basics, brush up on your skills and/or advance your career. 

Before you choose a course, make sure it’s a great fit. The best courses not only cover the material you’re looking for but start with the basics and include real-life scenarios. Most importantly, you can work at your own pace to gain a solid understanding of what’s being taught.