The 12 Best and Free Online Machine Learning Courses


Artificial intelligence is evolving at an ever-accelerating pace, and the need to keep up with it is extremely important. This boom in the data science space has catapulted the demand for skilled professionals in the market and has made data scientists one of the top-demanded profiles in the industry. The internet can be a very beneficial tool when it comes to acquiring new skills with its abundance of websites, tools, online courses, videos, and guides. Throughout this article, we’ll be discussing some of the best free online machine learning courses that will deliver a strong understanding of various concepts of machine learning and artificial intelligence. The addition of these trending and in-demand technologies into your portfolio can open new opportunities for you, transforming you into a skilled data scientist.

“Machine learning: a computer is able to learn from experience without being specifically programmed.”

– SupplyChainToday

What Makes a Really Good Free online Machine Learning Course?

Several platforms, such as Udemy, Coursera, edX, DataCamp, Udacity, and many others offer hundreds of free online machine learning courses. Out of this sea of courses, some praise-worthy courses shine brighter than others due to many reasons. Listed below are the criteria we used to narrow down our list to identify the free courses on machine learning:

  • Must be free
  • Must strictly focus on machine learning
  • Must explain how algorithms work
  • Must offer to learn at own pace and on-demand
  • Must use free or open-source tools and libraries
  • Must have a healthy amount of positive ratings from participants
  • Must provide practice questions and assignments
  • Must have engaging lectures taught by thought-provoking instructors

The Best Free Online Machine Learning Courses

After going through numerous free online courses, we have curated some of the best free courses on machine learning for you to fuel your curiosity and give you a head start in this domain. These courses can be undertaken by participants of all skill levels from beginners to experts and can be completed at their own pace to master machine learning.

1. Machine Learning — Coursera

Created by Andrew Ng, a globally-known Stanford professor and co-founder of Coursera, this course is one of the most successful & best free machine learning courses online. The numbers speak for the success; the course has almost 3.3 million enrollments, more than 35 thousand reviews, and an overall rating of 4.9 stars out of 5.

We highly recommend this course to anyone looking to dive into machine learning, data mining, and statistical pattern recognition. The course takes around 54 hours to complete and covers the following topics:

  • Parametric & Non-Parametric Algorithms
  • SVMs
  • Neural Networks
  • Recommender Systems
  • Dimensionality Reduction
  • Numerous case studies with real-world applications
  • Best practices in ML

One of the reviews about the course:

“Truly an exceptional class. Not often will someone with deep proficiency in a discipline have the time or incentive to share their insights and teach to others; this class is a rare exception, and given the vital importance of machine learning to the future, I have a great appreciation and debt to Andrew Ng.”

- — Nicholas D

2. AI for Everyone — Coursera

Offered by Andrew Ng, this course is ideal for anyone curious to understand the fundamental notions behind artificial intelligence and how it can impact you. Targeting non-technical participants, Andrew has gone into the details of how we can leverage the capabilities of artificial intelligence into our lives, and identify key pain areas to implement Artificial Intelligence. The course has 4.8 stars out of 5 and takes merely 6 hours to gain a comprehensive understanding of AI. The course covers:

  • Understanding of Ai
  • Identification and Implementation of AI at the workplace
  • Case studies for real-world applications
  • Impact of AI on society

“Machine learning is the most popular course for people from India. There is a window of time when India can embrace and capture a large fraction of the AI opportunity. But it will not remain open forever.”

– Andrew Ng

3. Learning From Data (Introductory Machine Learning) — edX

This course is from Caltech, one of the top science and engineering institutions in the world, shedding light on the practical implementations as well as the fundamental concepts behind machine learning. This course contains everything to prepare you with what machine learning is, the impact it has on the planet, and how you can start analyzing and implementing it. Some of the topics covered in this 10-week long course include:

  • Introduction to the topic
  • Algorithms
  • VC Dimension
  • Neural Networks
  • Regularization
  • Support Vector Machines
  • Linear Model
  • Learning Problem

4. Learn with Google AI

“Google AI is focused on bringing the benefits of AI to everyone.”

Offered by the search engine giant Google, Learn with Google is a hub of a carefully curated collection of resources on machine learning, including courses, videos, documentation, guides, tutorials, sample code, and hands-on experiences. These resources are crucial in understanding the various stages of machine learning development from ideation to deployment and are aimed at users with varying skill levels. Through this, Google aims to simplify machine learning for everyone by including essential topics such as:

  • Basic Introduction
  • Data Preparation
  • Clustering
  • Recommendation Systems
  • Problem Framing
  • TensorFlow
  • Fairness and Bias Identification
  • Real-world case studies

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Top Google AI Tools for Everyone

5. Deep Learning Course —

Yet another one of the best free machine learning courses by Andrew Ng, Kian Katanforoush, and Younes Bensouda Mourri, in collaboration with Nvidia, this course teaches deep learning to the masses. With 4.8 stars out of 5, this 4-month long course is among the top deep learning courses online. The’s partnership with Nvidia also brings a challenging project for the participants to gain industry-grade exposure that will hone their skills even more. Topics covered in this course include:

  • Convolutional Networks
  • RNNs
  • Dropout
  • BatchNorm
  • Case studies from healthcare, sign language reading, driving, NLP

“India has a large base of tech talent, and I hope that a lot of AI machine learning education online will allow Indian software professionals to break into AI.”

– Andrew Ng

6. Introduction to Machine Learning with R — DataCamp


               Image Source — DataCamp

This hugely popular course on DataCamp teaches you the ABCs of machine learning with participants from some of the top brands such as Dell, Intel, Siemens, and more. Assuming a strong background in R, this course covers a broad range of topics on machine learning to offer its participants a thorough understanding of the concepts with plenty of examples. Key highlights of this course:

  • Machine Learning basics
  • Prediction Models
  • Classification, Regression, and Clustering
  • Supervised & Unsupervised Learning
  • Bias & Variance
  • Measuring model performance
  • Interactive console for practice
  • Bundled datasets

7. Elements of AI — Helsinki University

Intended for the general masses, this well-received introductory course aims to eliminate the confusion surrounding artificial intelligence and related concepts by simplifying the technicalities of the topic for them. The reason behind this is to enlighten learners with artificial intelligence and its applications in the modern world. By igniting the curiosity to learn, more people can join this digital revolution, leading to better research and developments. This easy-to-access course covers:

  • Introduction to AI
  • Problem-solving with AI
  • Real-world applications
  • Machine Learning
  • Neural Networks
  • Implications

8. Data Science and Machine Learning Essentials Microsoft — edX

Jointly offered by Microsoft and experts from Duke University, this 6-week course on machine learning preps you with the core concepts of the technology. This course covers the various stages of data science, from data acquisition to visualization, for deploying it into the Microsoft Azure Machine Learning or Azure stack using Python or R for presenting a more hands-on experience. What you’ll learn from this course:

  • Introduction to Machine Learning
  • Understand data science and its various stages
  • Statistics and its use throughout ML
  • Practical usage of Microsoft Azure, Python, and R
  • Applied implementation of vital steps such as data ingestion, munging, exploration, regression, clustering

9. Machine Learning Crash Course — Google

“A self-study guide for aspiring machine learning practitioners”

Part of the Learn with Google platform, this course aims to get you up and running with machine learning within 15 hours with all of the fundamental concepts, including real-world examples with TensorFlow. Taught by some of the influential researchers at Google in an interactive manner, this course requires a prior understanding of some core concepts such as Python, Linear Algebra, Statistics, Calculus, and the use of console/terminal. Topics covered include:

  • Logistic Regression
  • Classification
  • Generalization
  • Neural Networks
  • Feature Crosses
  • Loss Reduction
  • Multi-Class Neural Networks
  • Static vs. Dynamic Training and Inferences
  • Practical Benefits of Machine Learning

10. Intro to Artificial Intelligence — Udacity

This 4-month long course from Udacity covers the essentials you would need to get a good grasp on artificial intelligence and other relevant topics. As an intermediate-friendly course, we recommend this if you have basic knowledge about AI and its implementations in the world. Paired with interactive quizzes and well-researched content, some of the concepts taught in this course are listed below:

  • Introduction to AI, ML
  • Logics behind algorithms
  • Statistics
  • Natural Language Processing
  • Computer Vision
  • Information Retrieval
  • Applications of AI in Robotics, NLP, CV, and other domains

11. Machine Learning with Python: From Linear Models to Deep Learning — edX

Part of a MicroMasters course in Statistics and Data Science by the profound instructors from MIT, this 15-week long course extensively covers the core notions behind machine learning that turns data into automated solutions. Targeted at intermediate learners with a solid foundation in Python, probability theory, calculus, and algebra, this course presents:

  • Core algorithms & their practical implementations
  • Representation
  • Probabilistic Modelling
  • Recommendation Problems
  • Support Vector Machines
  • Neural Networks
  • Projects exhibiting implementation of neural networks, reinforcement learning, and more

12. Creative Applications of Deep Learning with Tensorflow Kadenze — Class Central

This very famous course on Class Central, with 4.5 stars out of 5, takes you through deep learning, building algorithms while emphasizing the how and guiding amply on the what. This code-centric course uses TensorFlow to explain numerous concepts and algorithms, such as autoencoders, neural networks, along with their applications. Key takeaways from this course are:

  • Introduction to deep learning and model preparation
  • Neural Networks
  • Training models on datasets
  • Variational Autoencoders
  • Generative Adversarial Networks
  • Practical implementation of TensorFlow on a variety of concepts
  • Practical assignments included


Machine learning has already created a life-changing impact on us and has consistently proven that a vast majority of problems can be solved rapidly with the right data and a well-trained machine. Regardless of your current skill, the free online machine learning courses mentioned in this article give you an ample understanding of machine learning, the problems it solves, and its several underlying concepts. While some of the courses are for more advanced participants, some can be readily undertaken by many of us who are curious to learn.

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