Where to Learn Machine and Deep Learning for Free

Hello folks, if you want to learn Machine learning and Deep learning and look for the best online courses and tutorials, you have come to the right place. In this article, I will share some of the best free classes to learn machine learning and deep learning online.

By the way, If you are thinking of learning data science, machine learning, or deep learning, you are not alone; more and more people are starting with these advanced skills worldwide. I have seen a lot of interest from Software 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 1980s 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 show interest in machine learning and artificial intelligence to become part of the next technical revolution we may be witnessing.

If you are wondering what Machine learning and Deep Learning are, let me briefly overview them. 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 done by a Japanese programmer; you can read the full story here. On the other hand, Deep learning structures algorithms in layers to create an "artificial neural network" that can learn and make intelligent decisions independently. It's more complicated than machine learning.

While these free online courses are great, 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 fantastic, and you can buy in just $10 on Udemy sales.

10 Best Free Machine Learning and Deep Learning Online Courses for Beginners

Before I share the list of courses, I'd like to clarify that they are not of inferior quality even though these courses are free. They are just made free by their instructor for promotional and education purposes.

These courses are taken from popular online learning websites and platforms like Udemy, Pluralsight, Coursera, and FreeCodecamp. Some of them are also available for free on YouTube.

In fact, sometimes these free courses are covered in paid courses once the instructor reaches their promotional targets, so please be careful and check the course price before you join. Anyway, here is the list of the best free online courses to learn Machine Learning and Deep Learning from scratch by yourself.

The list includes the best free courses to not only learn machine learning basics but also relevant libraries like Kears, TensorFlow, Scikit learn, etc, all for FREE.

1. What is Machine Learning [FREE]

This is an excellent free course to learn essential Machine Learning concepts like Supervised, Unsupervised, and Reinforcement Learning with Python demo.

If you are new to Machine Learning, then this free Udemy course is perfect to start with. You will learn about the process of building supervised predictive models and make several of them using Python, the most widely used programming language for machine learning.

As part of the course, you'll receive the thoroughly annotated Jupyter Notebook used in the course. The best thing about this course is that concepts are presented with lots of examples, animations, and plots, making learning really easy, particularly for beginners.

I highly recommend this course to anyone who wants to learn Machine Learning from scratch. This is good for beginners and even for people with some experience who want to revise essential Machine learning concepts.

Here is the link to join this free course -

Machine learning by Andrew Ng in Coursera

This is one of the best free courses to learn Machine learning online. This is the course that taught me machine learning and more than 4 million people like me. Andrew Ng is one of the best teachers when it comes to Machine learning and deep learning as he explains these complex concepts in a way you can grasp, much easier than many of the paid courses I have gone through.

This free Machine learning course provides a broad introduction to machine learning, data mining, and statistical pattern recognition. This course is offered by Stanford University and it’s free to join, not just free to audit, but you will not get any certificates.

You will learn key machine learning concepts like Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks), Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning), and best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

here is the link to join this course - Machine learning by Andrew Ng

3. Practical Machine Learning with Scikit-Learn [Free Course]

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, also known as a skeleton, is particularly great for beginners. It offers a high-level interface for many tasks, allowing beginners to practice the entire machine learning workflow and understand the big picture better.

Anyway, in this course, you'll not only learn machine learning basics like what is a target variable or a feature but also, you'll learn how to create an end-to-end model using Python's SciKit Learn.

Here are key things you will learn in this course:

1. How to implement regression, classification, and boosting algorithms

2. Which algorithms work best for a given dataset

3. Data preprocessing

You'll get complete hands-on experience with the process of machine learning, which includes importing data, cleaning the data, training, and testing, pre-processing, and feature engineering.

Here is the link to join this free course -

In short, a perfect course for beginners to kick-start their machine learning journey. Once you know Sci-kit, you can explore more powerful libraries like TensorFlow on your own.

Introduction to Statistics by Guenther Walther on Coursera

This is another amazing free course that every person who wants to learn Machine learning, data science, deep learning, and AI should join, why because it teaches you Statistics which is very important for Data Science anything related to data, including machine learning.

This is another free course from Stanford University on Courser which you can join to learn Statistics like me and 100,0000 more people like me who have trusted this course for learning statistics.

In this course, you will learn about how to perform exploratory data analysis, understand key principles of sampling, and select appropriate tests of significance for multiple contexts. You will also gain the foundational skills that prepare you to pursue more advanced topics in statistical thinking and machine learning.

This course also teaches you topics like Descriptive Statistics, Sampling and Randomized Controlled Experiments, Probability, Sampling Distributions, and the Central Limit Theorem, Regression, Common Tests of Significance, Resampling, Multiple Comparisons.

here is the link to join this course for free - Introduction to Statistics by Guenther Walther on Coursera

5. Deep Learning Prerequisites: The Numpy Stack in Python V2 [Free]

This is another excellent free course to learn Deep Learning on Udemy. This covers four major Python libraries, like the Numpy, Scipy, Pandas, and Matplotlib stack, crucial to Deep learning, machine learning, and artificial intelligence.

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. At the same time, Matplotlib helps in looking at that data using some standard plots like the line chart, scatter plot, and histogram.

In this 1.9 hours long course, you will learn all these libraries and learn how to supervise machine learning (classification and regression) with real-world examples using Scikit-Learn.

Here are the main concepts covered in this course:

Basic operations in Numpy, Scipy, Pandas, and Matplotlib
Vector, Matrix, and Tensor manipulation
Visualizing data
Reading, writing, and manipulating DataFrames

You will also learn how to use Numpy, Scipy, Matplotlib, and Pandas to implement numerical algorithms. Most importantly, you will learn the pros and cons of various machine learning models, including Deep Learning Decision Trees, Random Forest, Linear Regression, Boosting, etc.

Here is the link to join this free course -

In short, an excellent free course to learn Deep Learning using Numpy, Scipy, Pandas, and Matplotlib stack.

Basics of Deep Learning [FREE Udemy Course]

This is another free deep learning course you can take on Udemy to learn the fundamentals of neural networks and the basics of Deep Learning. This 1.5-hour long course is taught by Sunil Kumar Mishra and it’s completely free, all you need is a free Udemy account to join this course.

This is also an introductory course and is suitable for beginners who know nothing about deep learning and want to start from ground zero. Along the way, you will learn about the evolution of deep neural networks and their application in areas like image recognition, natural language processing, etc

Here is the link to join this course - Basics of Deep Learning

7. Machine Learning Course for Beginners [FreeCodecamp]

This is another free online course to learn about Machine Learning concepts and its available for free on Youtube at freecodecamp's youtube channel.

This is a comprehensive 9 hour long Youtube course that is very similar to paid courses like Machine Learning A-Z: Hands-On Python & R.

This course will teach you the theory and practical application of machine learning concepts from scratch. This course is developed by Ayush Singh, a 15-year-old kid but you will admire his teaching skill and depth of knowledge.

⭐️ Course Contents ⭐️ ⌨️ (0:00:00) Course Introduction ⌨️ (0:04:34) Fundamentals of Machine Learning ⌨️ (0:25:22) Supervised Learning and Unsupervised Learning In Depth ⌨️ (0:35:39) Linear Regression ⌨️ (1:07:06) Logistic Regression ⌨️ (1:24:12) Project: House Price Predictor ⌨️ (1:45:16) Regularization ⌨️ (2:01:12) Support Vector Machines ⌨️ (2:29:55) Project: Stock Price Predictor ⌨️ (3:05:55) Principal Component Analysis ⌨️ (3:29:14) Learning Theory ⌨️ (3:47:38) Decision Trees ⌨️ (4:58:19) Ensemble Learning ⌨️ (5:53:28) Boosting, pt 1 ⌨️ (6:11:16) Boosting, pt 2 ⌨️ (6:44:10) Stacking Ensemble Learning ⌨️ (7:09:52) Unsupervised Learning, pt 1 ⌨️ (7:26:58) Unsupervised Learning, pt 2 ⌨️ (7:55:16) K-Means ⌨️ (8:20:21) Hierarchical Clustering ⌨️ (8:50:28) Project: Heart Failure Prediction ⌨️ (9:33:29) Project: Spam/Ham Detector

You can watch this course right here or on youtube, here is the link -

https://www.youtube.com/watch?v=NWONeJKn6kc

8. Introduction to Data Visualization with Seaborn [FREE DataCamp course]

Many available visualization libraries for python language, and another one used a lot for statistical visualization and customization is known as seaborn, which is used a lot among data analysts.

This free course is offered by Datacamp, a leading platform to learn data skills including machine learning You will learn to create a scatter plot and count and plots using the most capability of seaborn, which is adding a third variable to your plot. Later, you will learn to visualize two quantitative and categorical variables and customize your seaborn plots.

Here is the link to join this free course - Introduction to Data Visualization with Seaborn

9. Learn Keras: Build 4 Deep Learning Applications

This is an excellent free Udemy course to learn another powerful Python machine learning library called Keras. If you don't know, Keras is both a 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. It allows you to define and train neural network models in a few short lines of code, which is just awesome.

This free deep learning course will learn how to build an end-to-end Python machine learning project using Keras and tune a deep learning model and neural network.

The best part of this free online course is that the instructor walks through every line of code so you'll be able to understand the model and the process.

Here is the link to join this free course - Learn Keras: Build 4 Deep Learning Applications

10. How to Think About Machine Learning Algorithms [Free Trial]

If you don't know the question, you probably won't get the answer right, and this course is all about asking the right machine learning questions.

Machine learning is behind one of the coolest technological innovations today, but contrary to popular perception, you don't need to be a math genius to successfully apply machine learning.

At first, you need to identify whether machine learning can provide an appropriate solution, and in this course, you'll learn how to identify those situations.

The topics covered in this course include Classifying Data, Predicting relationships using regression, Recommending a product, and Clustering large data sets into meaningful groups.

By the way, You need a Pluralsight membership to access this course, which costs around $29 per month. On the other note, Pluralsight is a great resource, and its membership is definitely worth every penny spent. I have bought the annual membership, which comes with a discount.

Anyway, even if you don't have Pluralsight membership, you can still access this course for free by signing up for a 10-day free trial without any commitment, which provides 200 minutes of watch time.

Overall an excellent course to get a high-level overview of what machine learning is and how to use it to solve real-world problems. This is one of the basic Machine learning courses, but I have put that to the end because it's not entirely free.

11. Deep Learning Crash Course for Beginners [FreeCodecamp]

This is a free video course on Youtube to learn Deep Learning in 1 and half hours. This Deep Learning Crash Course for Beginners is taught by Jason Dsouza and its available for free on Freecodecamp's Youtube channel.

In this free deep learning course, you will learn the fundamental concepts and terminology of

Deep Learning, a sub-branch of Machine Learning.

This course is designed for absolute beginners with no experience in programming. You will learn the key ideas behind deep learning without any code.

You'll also learn about Neural Networks, Machine Learning constructs like Supervised, Unsupervised and Reinforcement Learning, the various types of Neural Network architectures, and more.

You can watch the full video here or on Youtube, it’s free

here is the link -

https://www.youtube.com/watch?v=VyWAvY2CF9c

What is the best Machine Learning free course?

The Machine learning course from Coursera is the best Machine learning free course in My opinion.

How do I get a free Machine Learning course?

Just join any of these free courses on Udemy, Coursera, DataCamp, and FreeCodecamp and start learning, no coupon is required.

What is the best course for Machine Learning?

When it comes to the best course, my vote goes to Machine Learning A-Z: Hands-On Python & R by Kirill Eremenko and his superdatasciece team for the sheer amount of depth, content, and quality. This course has over 44 hours of on-demand content and it is very high quality and touches almost all important areas of data science and machine learning.

Which is the best Machine Learning course for beginners?

In my opinion The Complete Machine Learning and Data Science: Zero to Mastery course by Andrei Negaoie is the best Machine learning course for beginners because of Andrei’s teaching style, course structure, quizzes, exercises, and amount of repetition you will get without getting bored.

Are Coursera certifications worth it?

Yes, they are completely worth it as they are provided by top-level universities and companies like Google. they hold value. They are not just a certificate of completion like many other platforms offer I mean Udemy. This means that the courses that you take through Coursera will be much more valuable to your future and your career.

Is Machine Learning a Good Career Path?

Yes, machine learning is a great career path if you're interested in data, automation, and algorithms as your day will be filled with analyzing large amounts of data and implementing and automating it. If money is important to you, a career in machine learning has an excellent base salary as well.

That's all about some of the best free courses to learn Machine Learning, Deep Learning, and Artificial intelligence. As I have said, these are new technologies which will rule the world in the coming years, hence learning them now will provide you with valuable experience and you will be well ahead of others.

At the moment, a Machine learning specialist is also drawing a very handsome salary and solving some interesting world problems. Hence, it's not only financially rewarding but also works is really great.

Other Programming Courses you may like

Thanks for reading this article so far. If you like these best free Deep Learning and Machine Learning courses, please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.

P. S*: If you are looking for the best Machine Learning course and don't mind paying some money, then Machine Learning A-Z: Hands-On Python & R is the perfect course to start with. This would be the right choice to learn Machine learning from scratch.*

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