12 Best Machine Learning Courses Online

There are a ton of options when it comes to studying algorithms, programming, and software. And one of the fastest-growing areas is Artificial Intelligence and Machine Learning. In this article, we’ll explore the best online courses for machine learning that can help you gain ML skills to enhance your career, boost your education goals, or ignite your personal interests.

But before we dive into which Machine Learning (ML) courses to take, what is machine learning?

What is Machine Learning?

Machine Learning* is a subset of Artificial Intelligence (AI) that uses statistics, mathematical models, and algorithms to create patterns to perform a specific task. Rather than hardcoding a process, a mathematical model learns over time without the need for explicit instructions. In business applications, sometimes predictive analytics is synonymous with machine learning.

Where can I learn Machine Learning Online?

There are a host of online sources for machine learning courses. Some of these courses are self-guided and learn at your own pace, while others have specific enrollment dates. Be sure to sign up prior to the enrollment date to have the best experience in the course. Let’s take a look at the best online courses for machine learning in 2020.

1. Machine Learning by Stanford with Andrew Ng (Coursera)

With over 2.87M students and a 4.9-star rating from 122,000+ students, it’s no wonder the Machine Learning course offered by Stanford is at the top of our recommendations list. This course will teach you how to approach machine learning to get computers to perform a task without being explicitly programmed.

You’ll gain skills in logistic regression, artificial neural networks, machine learning (ML) algorithms, and general machine learning best practices. The course is offered 100% online and you can start learning instantly at your own pace.

Details about the Course

There are 56 hours of lectures to watch, which are provided in an 11-week syllabus schedule. Because the course is flexible, you can take as much time on the course as you need to. The course is reviewed as being “extremely basic,” so if you’re new to the ML field, this will get you caught up to speed. However, if you’re looking for more advanced information, or you already have experience in ML, you’ll want to check out our list of advanced courses below.

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2. Data Science: Machine Learning, HarvardX (edX)

edX is another popular learning platform that connects students to professors from notable Universities. In the Data Science: Machine Learning course by HarvardX, you’ll learn the basics of machine learning and how it’s applied to real-world applications such as handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.

This course has you building a movie recommendation system using popular machine learning algorithms. If you’re looking for an applied way to learn machine learning, then I recommend checking out this course.

Details about the Course

Learn about training data, and how to use a set of data to discover potentially predictive relationships. The cool thing about this course is that it counts towards the Professional Certificate Program in Data Science offered through edX. Additional skills you can expect to learn are the basics of machine learning, how to perform cross-validation to avoid overtraining, popular machine learning algorithms, how to build a recommendation system, and regularization.

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3. Intro to Machine Learning (Udacity)

In Udacity’s Nanodegree, Intro to Machine Learning Nanodegree, you’ll learn foundational machine learning techniques including data manipulation to unsupervised and supervised algorithms. This isn’t a single course like the other options, but rather a “nanodegree”, that takes on average 3 months to complete. There are enrollment dates, so if you want to gain access to the next class, you’ll have to sign up by the deadline. Each month of the course covers a new topic: supervised learning, deep learning, and unsupervised learning. Each topic includes a practical project that you can use to get a feel for ML implementation.

Details about the Course

Intro to Machine Learning is designed for students with Python experience who haven’t explored topics in Machine Learning yet. Udacity recommends that you have at least 40 hours worth of programming experience, familiarity with data structures (dictionaries and lists), and experience with libraries including NumPy and pandas.

You’ll also need basic knowledge of probability and statistics for this course. Nanodegrees include real-world projects from industry experts, a 1-on-1 technical mentor, flexible learning programs, and personal career coach. I highly recommend going the Udacity route if you’re looking for a path that will improve your career and accelerate your learning.

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4. Machine Learning A-Z (Udemy)

Udemy is a great source for “quick and dirty” online courses. Anyone can be a teacher, provided that they have advanced skills in the area they’re teaching. I like using Udemy courses to fill in knowledge gaps or get up to speed on very niche subjects in a short amount of time.

In the Machine Learning A-Z course, you’ll master Machine Learning using Python and R. You’ll make accurate predictions, robust ML models, use ML for personal purposes, and handle specific topics including reinforcement learning, NLP, and Deep Learning. All you need is a high school mathematics background and the willingness to grind out 41-hours of on-demand video.

Details about the Course

The instructor, Kirill Eremenko, is a Data Science with over five years of industry experience and was trained by analytics mentors at Deloitte Australia. If you’re looking to bring Big Data to drive business strategies, this could be an interesting course to take. This course is designed for anyone interested in Machine Learning who wants to practice with real-life examples. The course also includes Python and R code templates that you can download and use for projects.

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5. Machine Learning with Python by IBM (Coursera)

If you’re looking for a career-oriented approach to learning Machine Learning, then you’ll want to check out the Machine Learning with Python by IBM course.There are two main components to this course:

1. First, you’ll learn about common applications in Machine Learning;
2. Secondly, you’ll learn about supervised and unsupervised learning, model evaluation, and common Machine Learning algorithms.

At the end of the course, you’ll have a portfolio of projects worth showcasing on a resume, LinkedIn, or job application.

Details about the Course

Completing the Machine Learning with Python course can be applied towards the IBM Data Science Professional Certificate or the IBM AI Engineering Professional Certificate. Additionally, if you choose to take this course and earn the Coursera course certificate, you will also earn an IBM digital badge, which looks really good from a professional advancement standpoint.

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Where can I learn Machine Learning Online for Free?

Just about all of the paid versions of the courses mentioned above have a free trial, free membership, or free version. If you’re looking for a course that will provide you information without having to pay and don’t mind limited access and not earning a certificate, then a free course on machine learning can get you started.

If you are using the course for career development or a promotion, it’s probably worth paying for the added certificate, specialization, or degree program. While it might seem like a lot shelling out thousands of dollars, some companies have education allowances and the value of a salary increase could make it well worth the initial investment. Just think about where a 5-10% promotion could land you! Especially if you’re the only person on staff with a data science or machine learning specialty.

There are a few great options for free machine learning courses online. You can always go the traditional route and use YouTube and blog articles to learn more about Machine Learning.

Machine Learning YouTube Channels

Some YouTube channels worth checking out are below:

• Siraj Rival
• Sentdex
• Machine Learning TV
• Pedro Domingo’s Lectures from University Washington

Machine Learning Websites

I also recommend these websites to learn Machine Learning online:

• Machine Learning Mastery 
• Indico
• Stats & Bots

While these resources are free, they require more dedication and patience and typically don’t provide the guidance that courses do. The biggest benefit to online courses is the ability to practice with projects and quizzes and to earn certificates that can be used for career advancement.

In this section, we will go over a few free online courses that you can enroll in that will provide a more guided experience when learning Machine Learning online. Here are the best machine learning courses that are free online.

1. Practical Deep Learning for Coders, v3 (Fast.ai)

Fast.ai is a comprehensive website for programmers looking to get into Machine Learning. This online course is set up more like a Wiki and is less about earning a certificate. That means you won’t have a login account, quizzes to submit, or lessons to watch. This is a great option if you’re looking for an online reference that’s entirely free and accessible from anywhere.Practical Deep Learning for Coders assumes at least a year of Python programming experience. According to Fast.ai, you don’t need much to get started with machine learning. All you need is “…one year of coding experience, a GPU and appropriate software, and that’s it. You don’t need much data, you don’t need university-level math, and you don’t need a giant data center.”

2. Machine Learning Scientist with Python (Datacamp)

Datacamp is an interesting website designed for professionals in the data science, artificial intelligence, and machine learning fields.You can subscribe to a Basic (free) account and gain access to the first chapter of every course, 100+ coding challenges, and 7+ projects. Datacamp also offers a mobile app for learning on-the-go. If you like their learning format, the enrollment is very affordable with plans starting at just $25/month.

3. Udemy

Udemy offers a selection of free Machine Learning courses as well. Visit Udemy.com and search “machine learning” at the top of the page. Then click on “All Filters” and select “Free” under the Price category.

Here are some free Machine Learning Courses on Udemy that are worth checking out.

4. Coursera

For the most part, Coursera courses are free to audit. If you want to participate in graded assignments or earn a Course Certificate, you’ll have to enroll in the paid version.To find free machine learning courses on Coursera, you can search for “machine learning” on their website.

5. Codecademy

Codecademy is similar to Datacamp. In addition to the Machine Learning course, they offer a bunch of programming and computer science courses to get you up to speed with best practices in coding.There’s a free plan that will give you access to the basic courses. For only $19.99 per month, you can upgrade and access members-only content, real-world projects, step-by-step guides, and peer support.

What are some advanced AI and Machine Learning courses online?

If you’re a more advanced programmer or engineer (have a Masters, Ph.D., or years of experience), then you’re probably past the basics of machine learning. In this case, I recommend checking out these advanced machine learning online courses.

1. Fast.ai Part 2: Deep Learning from the Foundations

Once you take Fast.ai Part 1, the next course is Part 2: Deep Learning from the Foundations. It takes you all the way from the foundations of implementing matrix multiplication and back-propagation, through to high-performance mixed-precision training, to the latest neural network architectures and learning techniques, and everything in between.

2. Advanced AI: Deep Reinforcement Learning in Python (Udemy)

This Expert-level Udemy course is designed to be a follow-up to the basic Machine Learning courses outlined in this article. In Advanced AI: Deep Reinforcement Learning in Python, you’ll master Artificial Intelligence using Deep Learning and Neural Networks.

3. Quantum Machine Learning (edX)

In this Advanced edX course, you’ll learn quantum machine learning algorithms using Python. With the rapid advances in machine learning and artificial intelligence, it’s natural to wonder whether quantum technologies can improve ML algorithms. By the end of this course, you’ll be able to tell the difference between quantum computing paradigms for machine learning; assess expectations for quantum devices on time scales; identify opportunities in machine learning for quantum resources, and implement learning algorithms on quantum computers in Python.

This is an advanced course and assumes you have a solid foundation in linear algebra, complex numbers, calculus, intermediate Python, and at least a background in one of the following: statistical mechanics, quantum physics, or machine learning.

Which Machine Learning Course will you take?

Are you thinking about taking an online Machine Learning course? Which one are you considering? Be sure to let me know in the comments below!