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If you want to learn how to build systems that learn from experience, then this article about free machine learning courses will shed some light on where you can learn the techniques to exploit data to create simple predictive models of the world.
The opportunities for people well versed with Machine Learning skills are exploding. According to Glassdoor, the average salary for a Machine Learning Engineer is $121,707.
First off, Mathematics is exceedingly critical in Machine Learning, so if you need to tighten your grips on the basics or advanced concepts, i’ve got your covered in this piece about the Math for Machine Learning and Data Science.
If you have some experience in programming, these courses will surely put you in a fast lane and help you fast-track your career in the field of machine learning.
However, if you are a beginner, i highly recommend that you check this article about Beginner’s guide to Machine Learning with Python or How to learn Artificial Intelligence, The Self-Starters way?
Please note, this compilation will be updated at least once every quarter to ensure that the courses are updated and relevant.
So, go ahead & save this one in your pocket/ bookmarks. ☆
The 3+ Best Free Machine Learning Courses on the Internet
I have complied these courses according to the student ratings, difficulty level and courses outline.
If you would like us to audit any free machine learning course that you feel should be listed in this piece, please let us know in the comments below!
CS229: Machine Learning – Spring 2019— Stanford
This course is designed by Stanford university to provide a broad introduction to machine learning and statistical pattern recognition.
Stanford is one of the best places to learn Machine Learning on the Internet. One of their Machine Learning Course by Andrew Ng has over 2 million enrollments and is highly praised and recommend for every Data Scientist and Machine learning Engineer.
Is it right for you?
This course assumes basic understanding of computer science and Python for Data Science (Numpy), and basic familiarity of topics related to Math for Machine Learning.
Upon the successful, you will be equipped with solid understanding Supervised learning, Unsupervised learning, Computational learning theory, reinforcement learning and adaptive control.
GO TO STANFORD
If you want to learn Python for Machine Learning, i’ve got you covered in this piece about A beginner’s guide to Machine Learning with Python.
Data Science: Machine Learning — Harvard
This introductory course on Machine Learning for Data Science is provided by Harvard University (HarvardX) and delivered via edX by Professor Rafael Irizarry.
This course will provide an introduction to machine learning and help learners to understand the important concepts behind performing cross-validation to avoid overtraining.
You will also learn about the popular machine learning algorithms, understand regularization and why it is useful in the field of machine learning.
Is it right for you?
This course is suitable for learners with some experience in Python and basic understanding of Data Science.
Upon the successful completion of this course, you will have a solid understanding of basic concepts required to build a recommendation system.
GO TO edX
Intro to Machine Learning — Udacity
This course on Machine learning is a part of Udacity’s Machine Learning Engineer NanoDegree. Created by Sebastian Thrun, Co-Founder of Udacity and Adjunct Professor at Stanford University, along with Katie Malone, Director of Data Science Research & Development at Civic Analytics.
In this course, you’ll start with Machine learning algorithms, analyzing and training data sets. And learn the end-to-end process of investigating data through machine learning lens.
Is it right for you?
Intro to Machine Learning is a Free Course and a recommenced prerequisite course for Machine Learning Engineer Nano degree Program offered by Udacity.
If you’re a beginner in Machine Learning with some Programming experience and background in Statistics, this course will help you skill yourself in machine learning.
Hands-on exercises and projects are central to the syllabus, so if you prefer hands-on learning, you’ll definitely love this course.
GO TO UDACITY
Machine Learning Crash Course
Machine Learning crash course from Google will introduce you to Google’s best practices in machine learning to help you get ahead in the field of machine learning. Created by Peter Norvig, Computer Scientist and Director of Research at Google INC.
You will learn to apply fundamental machine learning concepts, gain real-world experience with the companion Kaggle competition, and you can also Learn with Google AI to explore the full library of Machine Learning training resources to become a practitioner of the art.
Is it right for you?
This course will help you recognize the practical benefits of mastering machine learning and understand the philosophy behind machine learning.
This course features a series of lessons with video lectures, real-world case studies, and hands-on practice exercises. You will Learn best practices from Google experts on key machine learning concepts.
Also, Google Cloud is offering 2 Specializations on Machine Learning with TensorFlow or if you only want to Learn TensorFlow, i’ve got you covered in this piece about Best TensorFlow Courses.
GO TO GOOGLE-AI
Thanks for making it to the end 😉
If you liked this article, i’ve got a few practical reads for you. One about the Machine Learning Cheat Sheets and one about the Best (and Affordable) Machine Learning Courses the World-Class Educators.
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Course Images: Stanford, Google AI, Udacity, edX