Machine learning (ML) and artificial intelligence (AI) are gaining traction at a rapid pace across various industries, making these some of the most in-demand skills.
Fortunately, it’s never been easier to learn about machine learning from scratch or to enhance your existing skillset. The real question is where to sign up for a course.
To help you find the best options, we sifted through dozens of online machine learning courses and consulted with experts, industry professionals, and learners.
After extensive research, we’ve determined which courses are the most worthwhile.
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What to Expect From an Online Machine Learning Course?
Online machine learning courses mostly teach you programming languages, as well as various data science concepts. They also take you through the real-life implementation of these different techniques.
There are courses for learners of every level, with many of the courses being quite specialized. How in-depth you want to go depends on your career goals.
Most of the best online machine learning courses begin with an explanation of the general concepts and principles of ML, and progress to organizing and implementing the knowledge in machine learning projects.
You’ll also find sheets of prewritten code to assist you while you’re learning and practicing on different data sets.
If you want to find out more about starting a career in machine learning, have a look at the below video from a lecture by Andrew NG, Founder and CEO of Landing AI.
6 of the Best Machine Learning Courses Online
All the courses we’ve listed below were created in English. However, most of them offer subtitles in several languages for international learners too.
Let’s begin!
1. Machine Learning With Stanford University – Coursera
- Cost: Free access to all course materials except graded items. Certificate available for $49. Financial aid is available.
- Duration: +- 1 month (61 hours)
- Qualification: Upon completion, you’ll earn a shareable Coursera certificate.
This online machine learning course by Stanford University’s Andrew Ng is ideal for beginner and intermediate learners, providing a broad understanding of machine learning, data science, and data mining.
An attractive feature of this course, aside from the high-quality content, is the inclusion of case studies and practical examples for students to fully comprehend how machine learning principles are applied in real life.
This Coursera machine learning course made it to the top of our best ML courses list because of the promising learner career outcomes.
Out of the 4 million+ students who’ve enrolled in this program, 32% started a new career after completion of this course and 31% gained substantial career benefits.
The Machine Learning with Stanford course is divided into 4 weeks and each week takes approximately 2-5 hours to complete. There are also additional reading materials and quizzes you need to complete after viewing the video lectures.
You can adjust the deadlines for quizzes since the course offers you great flexibility in terms of scheduling.
2. Machine Learning for All – Coursera
- Cost: Free access to all course materials except graded items. Certificate available for $49. Financial aid is available.
- Duration: +- 1 Month (22 hours)
- Qualification: Upon completion, you’ll earn a shareable Coursera certificate.
Coursera’s Machine Learning for All is for absolute beginners who want to dip their toes in the machine learning waters.
Machine learning is one of the most complex domains of computer science but this course simplifies these concepts.
This Coursera machine learning course is ideal for students with a non-tech background who want to learn how ML is applied in their line of work and to understand its implications in a wider context.
You’ll also get to practice machine learning using beginner-friendly tools. But the main objective of this course is to learn advanced ML concepts, algorithms, and statistical pattern recognition.
In this course, you won’t cover any programming languages such as Python, R, or Java.
Towards the end of the course, you’ll have to complete a machine learning project using non-programming-based platforms.
3. Data Science and Machine Learning Bootcamp with R – Udemy
- Cost: $89.99
- Duration: 17.5 hours (128 total lectures divided into 35 sections)
- Qualification: Upon completion, you’ll receive a Udemy certificate.
R is a computer language that’s widely used for machine learning and data science operations. In this course, you’ll learn ML with R starting with the basics and advancing to an expert level.
The course covers a range of topics including using R for data sciences and specific machine learning projects, creating data visualizations, handling cvs. and SQL files and running algorithms with R.
The instructor for this online course has real-world experience in machine learning and has created dozens of Udemy courses, but none as comprehensive as this one.
This Udemy machine learning course is ideal for all; from beginner developers to experienced programmers. A great feature of this course is the prewritten code provided with each lecture, making it easy for you to practically apply the concepts you learn in each section.
You’ll find it easy to follow along with the lectures and can seek help from the various guides provided throughout the course.
The reading assignments recommended by the instructor are helpful if you want to truly master R for machine learning. Overall, the course is well-structured and one of the best online resources for aspiring machine learning students.
4. Machine Learning A-Z- Udemy
- Cost: $89.99
- Duration: 44 hours (320 detailed lectures)
- Qualification: Upon completion, you’ll receive a Udemy certificate.
Starting with the basic concepts of Python and R, this online machine learning course offers the best hands-on learning experience for new developers.
In this course, you get to practically apply your code and train on ML models throughout.
You’ll also develop skills on specific topics such as deep learning and gain expertise handling sophisticated machine learning techniques. The detailed 320 lectures will make you an advanced coder.
The most attractive feature of this Udemy machine learning course is that the code and lectures are updated regularly.
The course is designed for anyone interested in machine learning from young college software engineering students to experienced programmers moving into the domain of data sciences and ML.
Even if you’ve got rather limited coding knowledge and experience, you can still follow along and benefit from the course.
Both the instructors are experts in the industry and lectures are concise and offer detailed information.
5. Machine Learning With Harvard University – edX
- Cost: Enrollment is free. Paying $99 will give you access to the graded assignments and exams and a shareable certificate upon completion.
- Duration: 8 Weeks
- Qualification: HarvardX’s Data Science Professional Certificate
Offered by Harvard University, this course is part of a series of data science courses. Learn about machine learning algorithms, training data, and determining predictive relationships.
It’s ideal for beginners who want to develop the fundamental skills necessary for machine learning and data science careers.
With the course having detailed modules and being as rigorous as those offered on campus, you’re sure to advance your skills and gain a deeper understanding of machine learning by the end of the course.
6. Machine Learning With Python: From Linear Models to Deep Learning by MIT – edX
- Cost: Enrollment is free. By paying $300, you gain access to graded items and earn a certificate.
- Duration: 15 Weeks
- Qualification: MicroMasters certificate. Learners can also pursue an MIT Ph.D.
This online machine learning course is one of a four-part series in the MITx MicroMasters program in Statistics and Data Sciences.
The module and teachings are essentially the same as the on-campus courses, covering probability, machine learning algorithms, and artificial intelligence.
This course is for intermediate or advanced programmers. Prerequisites for joining this course include proficiency in Python, knowledge of probability theory, and a college-level understanding of vectors and metrics.
You’ll work on multiple real-world machine learning projects and gain a deeper comprehension of neural frameworks, mixtures, EM algorithms, VC-dimension, and more.
Consider enrolling in this edX online machine learning course if you want a high-level education and already have basic expertise in machine learning.
Conclusion
When picking one of the best online machine learning courses, pick a course that fits in with your specific career goals, while also considering factors such as the length and cost of the program.
The Data Science and Machine Learning Bootcamp with R is the most comprehensive course for different levels of learners. However, if you have a non-tech background and just want to understand ML instead of learning how to code then Machine Learning For All is a better choice.
To answer the question; which machine learning certification is best, we recommend From Linear Models to Deep Learning by MIT as it offers an accredited certification and the option to pursue a Ph.D. The Machine Learning with Harvard University course is also an excellent option for certification.
The Machine Learning With Stanford University has a proven track record of advancing the careers of its learners, while Machine Learning A-Z- Udemy is best for learning different programming languages.
For more online machine learning courses, search on Coursary.