10 Best Free Machine Learning Courses for Beginners to Join in 2023
Collection of best free online courses to learn Machine Learning for beginners from Udemy, Coursera, freeCodeCamp, and other online portals

If you want to learn Machine learning and Deep learning in 2023, and looking for free online courses and tutorials then you have come to the right place. Earlier, I have shared free Data Science Courses for beginners and In this article, I am going to share some of the best free resources to learn Machine learning and Deep learning online.
If you are starting with Machine Learning now then you are lucky that you have so many free and paid resources which can save you a lot of time and hassle. When I first started with Machine learning, I had a hard time figuring out how everything worked. What library is best for Machine Learning? Which algorithms worked best for which data set and there weren’t that many resources.
I spent a lot of time on tutorials, courses, and free resources to learn key machine learning algorithms and concepts. To save time for anyone who wants to learn Machine Learning, I have created this article with all the free resources you need to learn Machine Learning.
Btw, If you are thinking to learn Data Science, Machine learning, or Deep learning then you are not alone, more and more people are starting with these advanced skills around the world.
Though, I have seen a lot of interest from Indian engineers in machine learning and the Artificial intelligence space. They are totally caught up with the craze of developing programs that can recognize numbers, alphabets, vehicles, and several other image scanning stuff. The craze is very similar to what the 1980’s programmer has about video games, where moving a character on screen gives the joy you get when your program correctly identifies the number or letter you make from hand. From college graduates to junior programmers and from experienced programmers to software architects, all are showing interest in Machine learning and Artificial intelligence to become part of the next technical revolution, we may be witnessing. Btw, if you are wondering about what is Machine learning and Deep learning, then let me give you a brief overview. Machine learning programs use algorithms to parse data, learn from that data, and make informed decisions based on what it has learned. One example of that was selecting the best Cucumber from a lot, which was done by a Japanese programmer, you can read the full story here. On the other, Deep learning structures algorithms in layers to create an “artificial neural network” that can learn and make intelligent decisions on its own. It’s more complicated than machine learning.
Btw, if you don’t mind spending few bucks on learning a valuable skill like Machine learning then I also recommend you to check out Machine Learning A-Z: Hands-On Python & R if you need a comprehensive, in-depth course on Machine Learning.
This 45-hour course is the most complete resource to learn Machine Learning from scratch and you can buy in just $10 on Udemy sales, which is as good as free.
10 Best Free Machine Learning Courses for Beginners to Join in 2023
Before I share the list of courses, I’d like to clarify that, even though these courses are free, they are not of inferior quality, and they are just made free by their instructor for promotional and education purposes. In fact, sometimes these free courses are converted into paid courses once the instructor reaches their promotional targets, so please be careful and check the price of the course before you join. Anyway, here is my list of some of the best free online courses to learn Machine Learning and Deep Learning online by yourself.
1. Machine Learning By Andrew Ng [Coursera Free Course]
This is probably the best free online course to learn Machine Learning and most likely the most popular one as well. With more than 4 million people already joining this course it doesn’t need any introduction.
This course is created by none other than Andrew Ng, a pioneer in Machine Learning and Artificial Intelligence as well as one of Coursera’s founders. He has also authored many popular Coursera courses and certifications like Deep Learning Specialization and AI For Everyone, which is joined by millions of learners worldwide.
Coming back to the course, In this class, you will learn about the most effective machine learning techniques, gain practice implementing them and get them to work for yourself.
More importantly, you’ll learn about not only the theoretical underpinnings of learning but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.
Finally, you’ll learn about some of Silicon Valley’s best practices in innovation as it pertains to machine learning and AI. Coursera is also home to the best Machine Learning Certifications and if you want to become a master, Coursera is the best place to start with.
Here are the things which are covered in this course:
- Supervised learning
- Unsupervised learning
- Best practices in machine learning
The course will also draw from numerous case studies and applications so that you’ll also learn how to apply learning algorithms to building smart robots, text understanding, computer vision, medical informatics, audio, database mining, and other areas.
Here is the link to join this free course — Machine Learning

Btw, since this is a free course you won’t get any certificate. If you are joining to get Coursera certificate then you need to either enroll into the specialization or take a subscription plan like Coursera Plus which provides unlimited access to more than 5000+ Coursera courses, projects, and professional certificates.
2. Deep Learning Prerequisites: The Numpy Stack in Python V2
This is another excellent free course to learn Deep Learning and NumPy stack on Udemy. This covers four major Python libraries, like the Numpy, Scipy, Pandas, and Matplotlib stack, which are crucial to deep learning, machine learning, and artificial intelligence.
Created by Lazy Programmer Inc, creator of several Udemy best-selling courses on Udemy like Tensorflow 2.0: Deep Learning and Artificial Intelligence, this 2 hours long course will teach you all these libraries and learn how to supervise machine learning (classification and regression) with real-world examples using Scikit-Learn. You will also learn how to use Numpy, Scipy, Matplotlib, and Pandas to implement numerical algorithms, and most importantly, you will learn the pros and cons of various machine learning models, including Deep Learning, decisions Trees, Random Forest, Linear Regression, Boosting, etc.
If you don’t know, Numpy provides essential building blocks, like vectors, matrices, and operations on them, while Scipy uses those general building blocks to do specific things. Panda’s strength lies in loading data, particularly from the database, while Matplotlib helps in looking at that data using some standard plots like namely the line chart, scatter plot, and histogram. In short, an excellent free course to learn Deep Learning using Numpy, Scipy, Pandas, and Matplotlib stack.
Here is the link to join this course for FREE — Deep Learning Prerequisites: The Numpy Stack in Python V2

3. Practical Machine Learning with Scikit-Learn [FREE Course]
This is another free course from Udemy to learn Machine Learning and it focuses on SciKit-Learn. If you don’t know Scikit is one of the popular Python Machine learning libraries.
It was initially developed by David Cournapeau as a Google Summer of Code project in 2007, and since then, it has become the defacto machine learning library for many programmers. Scikit-Learn is particularly great for beginners as it offers a high-level interface for many tasks, which allows beginners to practice the entire machine learning workflow and understand the big picture better.
Once you know Sci-kit, you can explore more powerful libraries like TensorFlow on your own.
Anyway, in this course, you will learn multiple machine learning algorithms, along with data preprocessing, all in under an hour. You will go over regression, classification, component analysis, and boosting all in sci-kit-learn, one of the most popular machine learning libraries for python
Here is a list of Machine Learning Algorithms covered in this course:
- Linear Regression
- Polynomial Regression
- Multiple Linear Regression
- Logistic Regression
- Support Vector Machines
- Decision Trees
- Random Forest
- Principle Component Analysis
- Gradient Boosting
- XGBoost
In short, a perfect course for beginners to kick-start their machine learning journey.
Here is the link to join this free Udemy course —Practical Machine Learning with Scikit-Learn

4. Learn Keras: Build 4 Deep Learning Applications [Udemy Free]
This is an excellent course to learn another powerful Python machine learning library called Keras. If you don’t know, Keras is a both powerful and easy-to-use Python library for developing and evaluating deep learning models. It wraps the efficient numerical computation libraries like Theano and TensorFlow and allows you to define and train neural network models in a few short lines of code, which is just awesome.
Created by Adam Eubanks, this course is designed to get you up and running with deep learning as quickly as possible. We use Keras in this course because it is one of the easiest libraries to learn for deep learning. In each lecture, you will learn different machine learning algorithms and their use cases. The four algorithms which you will learn in this course are:
1. Linear Regression
2. Dense Neural Networks
3. Convolutional Neural Networks
4. Recurrent Neural Networks The best part of this course is that the instructor walks through every line of code so you’ll be able to understand the model and the process. If you are looking at a quick intro to deep learning, this course is for you.
Here is the link to join this free course — Learn Keras: Build 4 Deep Learning Applications

5. What is Machine Learning [Free Udemy Course]
This is an introductory course on Machine learning for beginners, who have no idea about Machine Learning. This free Udemy course provides a nice overview of Supervised, Unsupervised, and Reinforcement Learning with Python Demos
The course gives a big picture, (mostly) non-technical overview of Supervised, Unsupervised, and Reinforcement Learning. Ideas are presented using lots of examples with animations and plots and also a demo of course Python codes is presented
Students who would like to run and experiment with the demo codes will need to have a Google (or Gmail) account or have Python on their machine (can install the Anaconda platform). Knowledge of Python is not required to experiment with codes.
Here is the link to join this course — What is Machine Learning

6. 50 Must-Know Concepts, Algorithms in Machine Learning
This is another free course on Udemy to learn about Machine Learning. This course is designed to give you an introduction to the key Machine Learning concepts, Algorithms, and all the buzz words you keep hearing about Machine Learning.
If you want to get started with machine learning then this course will help you. It helps you to get ready for an interview with 50 concepts covering a varied range of topics. The course is intended not only for candidates with a full understanding of Machine Learning but also for recalling knowledge in data science.
The Structure of this course helps you to understand key concepts and get ready for an interview faster. It’s a good course to improve or refresh knowledge in machine learning
Here is the link to join this free course — 50 Must-Know Machine Learning Concepts

7. Learn Machine Learning algorithms, software, deep learning
This is another free Udemy course to learn Machine Learning and Deep Learning. This course covers deep learning, Neural Networks, KDD, AI, BI, ANN, Decision trees, Bayesian networks, TensorFlow, and Knime.
It’s also a great course to learn Machine Learning on Amazon Web Service our AWS and covers concepts of TensorFlow, Amazon SageMaker, and other AWS ML topics.
Unlike other free Udemy courses, this deep learning course is quite short and you will only have 54 minutes of content, which also makes it useful to learn key concepts quickly.
If you are looking for a crash course on Machine Learning for AWS then this is a perfect course for you.
here is the link to join this free course — Learn Machine Learning algorithms, software, deep learning

8. Scikit-Learn in 3 Hours [FreeCodeCamp + Youtube]
So far, I have included free online courses to learn NumPy and Kears and this free Udemy course will teach you Scikit-Learn, another popular Python library for Machine Learning.
Machine learning is a rapidly growing field. However, a lot of courses on the internet today do not go over some of its most powerful algorithms.
In this 3-hour long Scikit-learn full course, you will learn multiple machine learning algorithms, along with data preprocessing. You will go over regression, classification, component analysis, and boosting all in sci-kit-learn, one of the most popular machine learning libraries for python.
If you are looking for a free Sci-kit online course then you should watch this course and you can do it right here:







